Infodemic Disorder: Covid-19 Coping Strategies in Europe, Canada and Mexico 3031136977, 9783031136979

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Infodemic Disorder Covid-19 Coping Strategies in Europe, Canada and Mexico Edited by Gevisa La Rocca · Marie-Eve Carignan Giovanni Boccia Artieri

Infodemic Disorder

Gevisa La Rocca Marie-Eve Carignan Giovanni Boccia Artieri Editors

Infodemic Disorder Covid-19 Coping Strategies in Europe, Canada and Mexico

Editors Gevisa La Rocca Faculty of Human and Social Sciences Kore University of Enna Enna, Italy

Marie-Eve Carignan Department of Communication Université de Sherbrooke Sherbrooke, QC, Canada

Giovanni Boccia Artieri Department of Communication Sciences University of Urbino Carlo Bo Urbino, Pesaro-Urbino, Italy

ISBN 978-3-031-13697-9    ISBN 978-3-031-13698-6 (eBook) https://doi.org/10.1007/978-3-031-13698-6 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

1 Covid-19  and the Global Crisis of Information: an Introduction  1 Marie-Eve Carignan, Gevisa La Rocca, and Giovanni Boccia Artieri 2 Infodemic  Disorder: Covid-19 and Post-truth 15 Giovanni Boccia Artieri 3 A  Review of Some Covid-19 Pandemic Numbers in European Union, Canada, and Mexico 31 Fabio Aiello and Giovanni Boscaino 4 We  Are All Europeans. EU Institutions Facing the Covid-19 Pandemic and Information Crisis 65 Alessandro Lovari and Marinella Belluati 5 The  Practice of Emergency Gatewatching During the First Phase of the Pandemic. An Analysis Through the Tweets in Italian, Spanish, French and German 97 Gevisa La Rocca, Francesca Greco, and Giovanni Boccia Artieri

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6 The  Covid-19 Pandemic in Canadian Newspapers: An Analysis of the Journalistic Articles as Risk and Crisis Messages133 Olivier Champagne-Poirier, Marie-Eve Carignan, Marc D. David, Tracey O’Sullivan, and Guillaume Marcotte 7 Disinformation  in the Age of the Covid-19 Pandemic: How Does Belief in Fake News and Conspiracy Theories Affect Canadians’ Reactions to the Crisis?161 Marie-Eve Carignan, Olivier Champagne-Poirier, and Guilhem Aliaga 8 Analysis  of the Mexican Communication Plan to Control the Covid-19 Epidemic187 Olga Rodríguez-Cruz and Gabriela Rodríguez-Hernández 9 Social  Media Interactions in Mexico About the SARS-­ CoV-­2 Vaccination Plan219 Olga Rodríguez-Cruz 10 Rethinking  Our Interpretation Processes: Some Evidence253 Gevisa La Rocca, Giovanni Boccia Artieri, and Marie-Eve Carignan Index267

Notes on Contributors

Fabio Aiello  (PhD in Applied Statistics, University of Palermo), Associate Professor (Social Statistics—SEC-S/05), Kore University of Enna, Enna, Italy. Guilhem Aliaga  (MSc Université de Sherbrooke and Catholic University of Louvain), Research Professional at the UNESCO Chair in the Prevention of Violent Radicalization and Extremism. Giovanni  Boccia  Artieri (PhD), Full Professor in Sociology of Communication and Digital Media, Dean at the Dept. of Communication Sciences, Humanities and International Studies, Coordinator of the PhD program on Humanities, University of Urbino Carlo Bo, IT. Marinella  Belluati  Associate professor in Cultural and Communicative studies, Department of Cultures, Politics and Society, University of Turin, Italy. Giovanni Boscaino  (PhD in Applied Statistics, University of Palermo), Lecturer A (Social Statistics—SEC-S/05), University of Palermo, Palermo, Italy. Marie-Eve Carignan  (PhD University of Montreal and Institut d’Études Politiques d’Aix-en-Provence), Associate Professor with the Communication Department at Université de Sherbrooke. Olivier  Champagne-Poirier (PhD University of Quebec in Trois-­ Rivières), Assistant Professor with the Communication Department at Université de Sherbrooke. vii

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NOTES ON CONTRIBUTORS

Marc  D.  David  (MSc University of Montreal), Full Professor with the Communication Department at Université de Sherbrooke. Francesca  Greco  (PhD Sapienza University of Rome & University of Paris Descartes, USPC), Senior Assistant professor, Department of Languages and Literatures, communication, Education and SocietyDILL, University of Udine, Udine, Italy. Gevisa  La Rocca  (PhD University of Palermo), Associate Professor in Sociology of Communication and Culture processes, Faculty of Human and Social Sciences, Kore University of Enna, Enna, Italy. Alessandro  Lovari (PhD), Associate Professor in Cultural and Communicative Processes, Department of Political and Social Sciences, University of Cagliari (Italy). Guillaume  Marcotte (MSc Université de Sherbrooke and Catholic University of Louvain), Research professional at the Université de Sherbrooke. Tracey O’Sullivan  (PhD Queen’s University), Associate Professor in the Interdisciplinary School of Health Sciences, Faculty of Health Sciences, at the University of Ottawa. Olga  Rodríguez-Cruz  (PhD), Research Professor at the Universidad Autónoma de la Ciudad de México. Attached to the Bachelor of Comunicación y Cultura; Aggregate Professor at the Degree Course of Comunicación y Cultura. Gabriela  Rodríguez-Hernández (PhD), Research Professor at the Universidad Autónoma del Estado de México. Aggregate Professor at the Degree Course of Psicología.

List of Figures

Fig. 3.1 Fig. 3.2 Fig. 3.3 Fig. 3.4 Fig. 3.5 Fig. 3.6 Fig. 3.7 Fig. 3.8 Fig. 3.9 Fig. 3.10 Fig. 3.11 Fig. 3.12 Fig. 3.13

Weekly trend in the number of new cases of Covid-19 in Canada36 Weekly percentage variations in the number of new cases of Covid-19 in Canada 37 Weekly trend in the number of deaths due to Covid-19 in Canada38 Weekly percentage variations in the number of deaths due to Covid-19 in Canada 39 Weekly trend in the number of ICU admissions due to Covid-19 in Canada 40 Weekly percentage variations in the number of ICU admissions due to Covid-19 in Canada 41 Weekly trend in the number of new cases of Covid-19 in the European Union 43 Weekly percentage variations in the number of new cases of Covid-19, in the European Union 44 Weekly trend in the number of deaths due to Covid-19 in the European Union 45 Weekly percentage variations in the number of deaths due to Covid-19 in the European Union 46 Weekly trend in the number of new ICU admissions in the European Union 47 Weekly percentage variations in the number of ICU admissions due to Covid-19 in the European Union 48 Weekly trend in the number of new cases of Covid-19 in Mexico50

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List of Figures

Fig. 3.14 Fig. 3.15 Fig. 3.16 Fig. 3.17

Weekly percentage variations in the number of new cases of Covid-19 in Mexico 51 Weekly trend in the number of deaths due to Covid-19 in Mexico52 Weekly percentage variations in the number of deaths due to Covid-19 in Mexico 53 Weekly trend in the number of new cases per million people of Covid-19 in Canada (___), European Union (__o__), and

Fig. 3.18

Mexico (...o...)56 Weekly trend in the number of deaths per million people due to Covid-19 in Canada (___), European Union (__o__), and

Fig. 3.19

Mexico (..o..)58 Weekly trend in the number of new ICU admissions per million people in Canada (___), European Union (__o__)59

Fig. 3.20 Fig. 3.21 Fig. 4.1 Fig. 5.1 Fig. 5.2 Fig. 5.3 Fig. 5.4 Fig. 5.5 Fig. 6.1 Fig. 6.2 Fig. 6.3 Fig. 7.1 Fig. 7.2 Fig. 7.3 Fig. 7.4 Fig. 7.5 Fig. 7.6 Fig. 7.7 Fig. 7.8 Fig. 7.9 Fig. 7.10 Fig. 8.1

Weekly Rt index’s trends in Canada, the European Union, and Mexico61 Boxplot of Rt estimates by area 62 European Communication Ecosystem. Source: Authors’ property74 Symbolic space emerging from the Italian corpus 111 Symbolic space emerging from the Spanish corpus 112 Symbolic space emerging from the French corpus 113 Symbolic space emerging from the German corpus 122 The gatewatching of emergencies. Source: Reworking starting Bruns’s scheme (Bruns, 2008) 127 Authors of the articles (A total of 455 articles in the corpus did not mention the author) 148 Use of direct quotations 152 Use of indirect quotations 152 Mean level of belief in the five conspiracy statements 170 Mean level of belief in the six fake news items 171 Distribution of the respondents according to the thresholds 172 Belief in the indices by gender 173 General belief in the indices by age group 174 General belief in the indices by education level 175 General belief in the indices by country of birth 175 Proportion of general belief by news source 178 Average compliance according to overall belief in the indices 179 Vaccine refusal or hesitancy by group 180 Post by López-Gatell. Source: Public domain image taken from the Undersecretary’s social media profile 195

  List of Figures 

Fig. 8.2 Fig. 8.3 Fig. 8.4 Fig. 8.5

Fig. 8.6 Fig. 8.7 Fig. 9.1

Fig. 9.2 Fig. 9.3

Fig. 9.4 Fig. 9.5 Fig. 9.6 Fig. 9.7

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Mexico’s President Andres Manuel Lopez Obrador shows his amulets. Source: Public domain image taken from the website of the Office of the Mexican President 198 First appearance of Susana with the mask. Source: Public domain image taken from the SuSana Distancia campaign (Undersecretary Hugo López-Gatell. August 14, 2020) 204 Susana invites you to maintain interpersonal distance. Source: Public domain image taken from the Ministry of Communication and Transport (SCTMexico, April 15, 2020c) 205 Susana explains that only one person per family can leave the house out of necessity. Translation: It is important that only one person per household goes out to buy groceries or medicines. Source: Public domain image taken from Mexican Ministry of Health, December 16, 2020 206 SuSana Distancia—timeline. Source: The graphic design of the timeline was created by Mariana Padilla Martínez 210 ¡Quédate en casa!—advertising poster. Source: Public domain image taken from the SuSana Distancia campaign 213 Posts related to episode 2 on Facebook. Source: The table was developed by the author. Interruptus Radio’s original post: https://m.facebook.com/story.php?story_fbi d=1781809678662117&id=464224880420610&sfnsn=s cwspwa229 Posts related to episode 2 on Facebook 230 Posts related to episode 4 on Facebook (The information can be consulted at the following Facebook page: https://m. facebook.com/story.php?story_fbid=292618052219552&i d=100044140794092&sfnsn=scwspwa. The information can be consulted at the following Facebook page: https://m. facebook.com/story.php?story_fbid=273015357519841&i d=100044341360428&sfnsn=scwspwa). Source: The table was developed by the author using information available at Lorenzo Meyer’s and Sergio Aguayo’s Facebook walls: https://m.facebook.com/story.php?story_fbi d=292618052219552&id=100044140794092&sfnsn=scws pwa (Meyer) and https://m.facebook.com/story.php?story_ fbid=273015357519841&id=100044341360428&sfnsn=scws pwa (Aguayo) 231 Type of reply 233 Type of reply 234 Type of replies 235 Type of reply 235

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List of Figures

Fig. 9.8 Fig. 9.9 Fig. 9.10 Fig. 9.11 Fig. 9.12 Fig. 9.13 Fig. 9.14 Fig. 9.15 Fig. 10.1 Fig. 10.2 Fig. 10.3 Fig. 10.4

Type of reply 235 Type of reply 236 Type of reply 236 Type of replies 238 Man’s replies 239 Women’s replies 239 Example of participation 242 Example of participation 242 Nested case study for infodemic disorder 255 The tree of similarity 259 Dendrogram: representation of classes, frequencies (F) of words and the extent of association to the class (χ2)262 Lexical correspondence analysis built on two factors (factor 1: 26.27%; factor 2: 22.35%) 263

List of Tables

Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 6.1 Table 6.2 Table 6.3

Summary statistics of new cases, deaths, ICU admission, by wave, in Canada 35 Summary statistics of new cases, deaths, ICU admission, by wave, in the European Union 42 Summary statistics of new cases, deaths, ICU admission, by wave, in Mexico 49 Some demographics of Canada, the European Union, and Mexico54 Summary statistics of new cases, deaths, ICU admission, and effective reproduction rate, Rt, by wave, for Canada, the European Union, and Mexico 55 Timeline of the main events of March 2020 in the four countries99 Descriptive characteristics of the dataset from March 4–11, 2020105 Cluster analysis and correspondence analysis results and sentiment description for Italian tweets 108 Cluster analysis and correspondence analysis results and sentiment description for Spanish tweets 109 Cluster analysis and correspondence analysis results and sentiment description for French tweets 109 Cluster analysis and correspondence analysis results and sentiment description for German tweets 110 List of the 19 protagonists or groups identified in the analyzed articles 140 The 25 major themes addressed in the articles 141 Journalistic intentions inherent in coverage of the pandemic 142 xiii

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List of Tables

Table 6.4 Table 6.5 Table 7.1 Table 7.2 Table 7.3 Table 8.1 Table 8.2 Table 8.3 Table 8.4 Table 8.5 Table 8.6 Table 8.7 Table 8.8 Table 8.9 Table 8.10 Table 8.11 Table 9.1 Table 9.2 Table 9.3 Table 9.4 Table 9.5 Table 9.6 Table 9.7 Table 9.8 Table 9.9

Discursive strategies used to cover the pandemic 143 Scope of the sample 145 Index thresholds 172 Correlations with news sources 177 Associations between indices and trust in health experts, political authorities, and the media 181 The four objectives of the CSCP 188 The phases of the pandemic in Mexico 191 Elaboration of the corpus study, including statements and SuSana Distancia television spots 193 Description of some audiovisual commercials of SuSana Distancia202 Phrases used to appeal to responsibility 206 Phrases used in three of the spots to convince people to stay safe at home 207 Phrases used in the spots 207 April spots featuring Stay at home 208 Spots of May that play with emotional language 208 May commercials that contain Stay at home 209 Spots of December that play with emotional language 209 Stage of vaccination in Mexico 220 Distribution of participants by gender and social media 232 Distribution of participants by gender and social media 232 Distribution of participants by gender and social media 233 Distribution of participants by gender and social media 236 Distribution of participants by gender and social media 237 Distribution of participants by gender and social media 240 Number of political-aggressive replies 241 Number of political-aggressive replies 244

CHAPTER 1

Covid-19 and the Global Crisis of Information: an Introduction Marie-Eve Carignan, Gevisa La Rocca, and Giovanni Boccia Artieri

As early as January 2020, even before the World Health Organization (WHO) considered that the severity of the disease allowed it to qualify it as a pandemic, the organization’s Director General, Tedros Adhanom Ghebreyesus, declared Covid-19 an international public health emergency and many countries triggered a state of health emergency (Milasin & Baert, 2020). The flow of information circulating about this new coronavirus at the time was particularly important, both on socio-digital

M.-E. Carignan (*) Department of Communication, Université de Sherbrooke, Québec, Canada e-mail: [email protected] G. La Rocca Faculty of Human and Social Sciences, Kore University of Enna, Enna, Italy e-mail: [email protected] G. Boccia Artieri Department of Communication Sciences, Humanities and International Studies, University of Urbino Carlo Bo, Urbino, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. La Rocca et al. (eds.), Infodemic Disorder, https://doi.org/10.1007/978-3-031-13698-6_1

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networks and on the Internet, where traffic was increased by 60% in some countries (OECD, 2020), as well as in traditional media, to a point where Lalancette and Lamy (2020) were watching an unprecedented media eclipse in Canada, as all the news revolved around the pandemic and its effects. Roy (2021) observed the same phenomenon of media eclipse occurring in the content published by the Francophonie news media present on the Instagram platform. This media overkill of Covid-19 was also already raising concerns among various researchers noting the challenges faced by press companies already precarious and economically shaken by the pandemic as well as information professionals overworked in a context that sometimes put their own health at stake, while the risks of slippage are significant when it comes to health-related information (Caron-Bouchard & Renaud, 2010; Lacroix & Carignan, 2020; Le Cam et al., 2020). On the other hand, the coming fatigue reactions among part of the public in the face of this massive coverage, implying a potential lack of interest in this news, were cause for concern because of their potential consequences on adherence to the health measures put in place as well as on the perception, among a fringe of the population, of a disproportionate media coverage of the pandemic. Nevertheless, the fact that this virus is new and therefore unknown, coupled with the fact that society had not had to deal with a pandemic of this magnitude for several years,1 raised a need to quickly obtain information about it. Research has followed one another at an accelerated pace, allowing important knowledge about the virus, vaccines and potential treatment to be developed at an unprecedented speed, but also leading to certain errors in the methodologies put in place in a sometimes-hasty manner and in the accelerated revision processes of scientific articles.2 These mistakes may have generated confusion and mistrust among part of the public. Plunged into this highly anxiety-provoking situation, despite a media overkill of the measures put in place, but also in front of the fact that the 1  For the World Health Organization, this health situation is the most serious that has been announced since 2005, when the Global Alert System for International Public Health Emergencies was set up. 2  Prestigious journals such as The Lancet or the New England Journal of Medicine have retracted articles related to Covid-19, whose data were considered dubious. These withdrawals can have a significant impact on public confidence in science.

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media expose the current lack of knowledge surrounding the emergence of the virus and the potential treatments, the public then seeks by all means to understand what is happening now and anticipate the future. However, the phenomenon of disinformation already observed during recent epidemics (Smallman, 2015; Abramowitz et al., 2017) disrupts the information ecosystem like never before, due to the number, diversity, scope and impacts of erroneous or misleading news that is conveyed (Monnier, 2020), not to mention that conspiracy theories already observed during other epidemiological crises seem to be spreading even faster in the context of the global pandemic (Reichstadt & Fourquet, 2020). Thus, several researchers have observed a rise in conspiracy speeches about the pandemic (de Coninck et al., 2021), that is, discourses that explain events by the secret and malicious action of a group of individuals (Dentith, 2014). This link between distrust of the authorities and adherence to conspiracy theories is documented in several studies (Luhmann, 2006; Renard, 2015). Indeed, people who have a predisposition to reject information from official sources or experts, including in the context of the global pandemic, would be more likely to adhere to conspiracy theory (Uscinski et al., 2020). Getting regular information on social networks is also associated with “an increased risk of generalized anxiety or major depression” (Généreux et al., 2020). The frantic research and production of knowledge and information about Covid-19 has thus quickly led to a situation that the WHO has described as an infodemic (contraction of the words information and epidemic), a context of overabundance of information, of very variable veracity, concerning a problem of public order and particularly topical, which hinders its resolution by preventing the general population from finding information reliable and act accordingly (OQLF, 2020). WHO believes that this outbreak of disinformation is a second enemy to be combated as it harms the public’s quest for trusted information and complicates the conduct of emergency response. “False information spreads faster and easier than this virus, and it is just as dangerous”, the WHO Director General said at a conference in Munich (WHO, 2020a). Indeed, in the context of the pandemic, reliable information regularly rubs shoulders with disinformation and misinformation, phenomena that we will define in more detail in the first chapter of this book.

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This massive disinformation has sometimes led to an intensification of discrimination and hate speech against certain cultural communities or individuals who were wrongly associated with the virus or its spread. Several researchers are concerned about the consequences of this infodemic relating to the global pandemic, which can create social panic, a climate of mistrust towards governments and public institutions, as well as a destabilization of democratic systems, in addition to harming citizens’ decision-making (Carignan et al., 2022). This distrust of institutions also leads to distrust of official sources of information, such as media companies, which many individuals accuse of colluding with the public authorities and of being funded by the latter. This loss of trust in institutions, coupled with a sense of fear, can influence the level of public support for the recommendations of public health authorities, in addition to facilitating adherence to conspiracy theories (Limaye et al., 2020; Miller, 2020). Especially since the crisis has not been managed in the same way between countries. The epidemiology and public health strategies put in place differ greatly from each other, and even within countries, while WHO calls for coordinated efforts by the international community (WHO, 2020b). In addition to offering a very different epidemiological picture, these countries have used distinct public health strategies, including screening, containment and deconfinement and vaccination. Similarly, they have used a wide variety of communication strategies to respond to the crisis, which sometimes causes controversy and confusion among the population, not to mention that not all governments have reacted in the same way to the crisis. Indeed, several authoritarian countries have taken advantage of the pandemic to increase media censorship, which has harmed the international management of the pandemic and has sometimes prevented a fair picture of the evolution of the pandemic situation (Reporters without Borders, 2020). Journalists from all continents have been the target of intimidation, verbal attacks, detentions ordered by authoritarian regimes or withdrawals of accreditation while covering pandemic news (Reporters without Borders, 2020). In addition, some heads of state have downplayed the seriousness of the virus or the pandemic situation, going so far as to make inaccurate and sometimes even false statements that may have misled citizens and fueled information chaos. For example, Donald Trump, former president of the United States, had suggested that the virus would disappear with the heat of summer and proposed that research be conducted to verify the effectiveness of disinfectant injections to fight the coronavirus (Biron, 2020; de

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Lancer, 2020).3 In Brazil, President Jair Bolsonaro, “has urged Brazilians to ‘return to normality’ in several occasions, ignoring growing empirical evidence about the positive effects of social distancing” (Ricard & Medeiros, 2020) and has been seen as the leader of the “coronavirus-­ denial movement” (Friedman, 2020) and promulgated the effectiveness of treatments such as chloroquine or hydroxychloroquine to combat Covid-19. These examples demonstrate how the public was subjected to contradictory information and how some populations around the world may have struggled to access facts rigorously verified by independent sources during the outbreak of the health crisis, with some politicians sometimes even reinforcing the conspiracy ideologies adopted by a fringe of the population. Therefore, it was appropriate, in the context of this book, to look at how the different actors, whether governments, public health authorities or the media, for example, have managed this public health crisis coupled with a communication crisis. It is also relevant to look at how people have reacted to it, both on socio-digital platforms and individually, trying to understand how fake news and conspiracy narratives may have affected their perception of the situation. The comparative and international perspective adopted by this book, which will take a look at Europe, Canada and Mexico, will allow us to observe the best practices that have been adopted, the emerging and adaptive communication strategies (Mintzberg, 2007) as well as the mistakes that may have been made in different contexts to draw lessons that will undoubtedly be very useful for the management of future public health crises. Differences in the way the pandemic was managed and the level of responsibility of local, regional, provincial or national actors, in addition to the fact that each of these places experienced similar virus prevalence rates but peaks of infection at distinct times, make this comparison even more relevant. In this context, this book aims to connect two dimensions: public communication and research as well as sharing of information by citizens during the Covid-19 pandemic. To achieve this, the book is divided into chapters, which aim to analyze the communication strategies of public institutions and the communication of citizens. 3  Numerous poisonings related to the ingestion of disinfectant have been reported in the United States, resulting in the deaths of at least four people (Associated Press, 2020). WHO has issued public warnings to this effect and added an infographic on the ingestion of disinfectant on its myth busters available online.

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The aim of this book is to pull off the construction of information processes during the Covid-19 pandemic. To achieve this final goal, the book is divided into a path that proceeds from the general to the particular. More specifically, in the next chapters, we will approach the situation from different angles, developing a triangulation of research sources and methods. AoIR’s ethical guidelines (2019) have been followed in using sources, data, posts, tweets and other materials from the Internet in this volume. The second chapter, signed by Giovanni Boccia Artieri, will return to some of the elements discussed in the introduction and will focus more specifically to outline the main elements of the public and academic debate connected to the themes of “fake news,” “misinformation,” “disinformation,” “media manipulation,” “conspiracy theory,” “coordinated inauthentic behavior” and “propaganda” that are all intertwined in digital platform ecosystems. Reference is made here to the problem that afflicts the information field and which is defined by three interrelated issues disinformation, misinformation and propaganda (Born & Edgington, 2017). The look in this chapter on these informational issues will make it possible to better master the concepts evoked later throughout this book, in addition to being at the heart of the infodemic related to the Covid-19 health crisis. The third chapter of this book, written by Fabio Aiello and Giovanni Boscaino, focuses on the spread of the coronavirus. As the authors recall, this pandemic situation has shown that a health crisis that seems very limited geographically, at least in its early stages, can quickly gain momentum and spread throughout the globe, especially in this era of globalization, reminding us that we live in a society of internationalized risks. As we mentioned at the beginning of the introduction, the spread of the contagion and the actions implemented by local governments to counter it seems to have been rather heterogeneous. Therefore, it may be useful to understand how different some of the characteristics of the spread of the infection have been in different areas of the world. To better understand the situation, the authors propose a purely objective approach, referring to the purely quantitative aspect of the contagion, a description of both the size and the speed of the contagion albeit limited to three different geographical macro-areas: the States of the European Union, Canada, Mexico. Their analysis allows us to identify a common trait for these three geographic contexts so different from each other, in the period under analysis in this volume. In effect, the three areas were characterized by reasonably similar virus prevalence rates. Instead, their fluctuations are recognized as

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a symptom of the effects of restrictions (imposed or relaxed), the impact of new virus variants, and individuals’ behavior. Starting from Chap. 4 and up to Chap. 9, two dimensions are analyzed for each geographical context in order to outline how information disorder has developed and been faced by public institutions and citizens. The observation period is for all three geographical contexts: the first stage of the Covid-19 pandemic. The third and fourth chapters are dedicated to Europe. In the Chap. 4 of this book, Alessandro Lovari and Marinella Belluati investigate how the European Institutions have faced the Covid-19 pandemic from a communication point of view, focusing the attention on policies, strategies and interventions addressed to counteract disinformation and the spread of problematic messages that could harm citizens and weaken democracy. Chapter 5 is dedicated to the analysis of the tweets shared in Italian, French, German and Spanish, during the period preceding the first of the European lockdowns, between March 4 and 11, 2020, on the social network Twitter. Gevisa La Rocca, Francesca Greco and Giovanni Boccia Artieri demonstrate how the arrival of the virus in Italy has been understood and discussed in other European Union countries, including France, Spain and Germany, as well as outside the continent. Italy was the first country in Europe affected by the virus and the death toll in the country has been considerable. The situation in that country has had repercussions on the understanding and management of the crisis around the globe. It is therefore particularly relevant to understand how this management has been perceived and treated by citizens. This chapter allows to observe the feelings experienced, to analyze the reflections carried out in those first hours and to investigate the discussion topics of those who saw the Covid-19 spreading in their daily reality. It will also allow us to understand how, starting from the first Italian cases and the lockdown introduced by Italy, the other three European countries have begun to prepare for the impact of the first wave of the pandemic. Chapters 6 and 7 are dedicated to Canada and also explore the two dimensions: that of institutions (Chap. 6) and that of citizens (Chap. 7). In Chap. 6 of this book, Olivier Champagne-Poirier, Marie-Eve Carignan, Marc D.  David, Tracey O’Sullivan and Guillaume Marcotte analyze the dense media coverage of the pandemic by Canadian dailies. Using an inductively built coding grid, the authors analyzed 5055 journalistic articles published by 20 Canadian daily newspaper in the three months following the outbreak of the virus in Canada (January 27 to April 27, 2020);

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this approach allowed them to statistically describe qualitative processes in which numerous protagonists were staged, different facets of social reality were exposed and journalists positioned themselves as news professionals. As mentioned earlier in the introduction to this book, the media have a key role to play in crisis and risk communication, especially during a pandemic (David & Carignan, 2017; Hanitzsch & Vos, 2018; Olsen et al., 2020). This chapter allows a clear view of the role of the Canadian press in the risk and crisis communication surrounding the pandemic. Referring to the IDEA model for effective instructional risk and crisis messages (Sellnow & Sellnow, 2014), this analysis shows in particular that it is apparent that Canadian newspaper messages have little potential to contribute to the “Internalization” of the crisis by certain high-risk groups and that they focus very little on the “Actions” that individuals can take to protect themselves from pandemic-associated risks. This chapter reminds us of the relevance of examining journalistic coverage to better understand risk and crisis communication in the context of a pandemic. They also highlight the impact of risk and crisis messaging as a central consideration for research. Chapter 7 of this book, signed by Marie-Eve Carignan, Olivier Champagne-Poirier and Guilhem Aliaga, also focuses on the situation related to the pandemic in Canada. Considering the context of massive disinformation mentioned earlier in the introduction concerning the Covid-19 pandemic, the purpose of this chapter is to better understand the level of belief in disinformation and conspiracy theories in the Canadian context, as well as the factors impacted by this belief. This analysis is based on data collected in a population-based questionnaire survey conducted to gain a better understanding of the impact of the pandemic on Canadians. The survey shows that respondents’ gender, education and country of birth have little impact on belief in conspiracy theories and fake news associated with the Covid-19 pandemic, although some findings are more salient among certain groups of respondents. Considering the communication and news habits of the respondents, the authors found out that those who use governmental and traditional information sources (media, press) will tend to believe less in conspiracy theories and fake news. Conversely, individuals who turn to the Internet and social media to get informed exhibit greater belief in these elements. Finally, trust in public authorities, especially health experts, appears to be lower among individuals who subscribe to conspiracy theories and fake news, which invites reflection on the impact of mistrust of institutions in crisis management. This lower trust goes hand in hand with health behaviors, particularly

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vaccine hesitancy and non-compliance, which are more present among individuals who believe in conspiracy theories and fake news. Chapters 8 and 9 are dedicated to Mexico and follow the same dimensions addressed in the other studies. Mexico had the third place in the Americas (only below the USA and Brazil) based on the number of infections and deaths, and it was the first Latin American country to start vaccinating its population. Chapter 8 of this book, written by Olga Rodríguez-Cruz and Gabriela Rodríguez Hernández, takes a look at the situation in Mexico. This chapter uses discourse analysis to study the statements made by two main players of the Mexican government: President Andrés Manuel López Obrador and Hugo López-Gatell, the Undersecretary of Health Prevention and Promotion. This analysis also discusses the ¡Quédate en casa! audiovisual advertisement campaign and its main character: the heroine SuSana Distancia. This chapter concludes that the government’s advertisement campaigns fail to promote the importance of health care and the community’s joint responsibility among the community; this is reflected on the number of people infected and deaths in Mexico and that the Mexican government never had the intention of promoting the use of masks as an essential measure. Two spots taught the population how to wear a mask; however, the discourse of both the Undersecretary and the President was that wearing a mask was not an essential measure to control infections. As a result of the contradictions between the messages and the actions of health and government leaders, the population did not receive clear information about the measures they should take if they caught the SARS-CoV-2 virus. These contradictions created ambiguity among the population. In Chap. 9, Olga RodríguezCruz discusses the implementation of the Federal Government’s Vaccination Plan in Mexico. The objective of this chapter is to study the interactions carried out in two social media (WhatsApp and Facebook) in order to analyze what people think about the way this Plan has been implemented. A mixed methodology was used to carry out this analysis in order to gather the data and carry out a numerical visualization with the aim of obtaining a general appraisal about the study object. Additionally, digital ethnography was used to observe the type of interaction carried out in the fora. The data was gathered during three episodes. The first episode included informants, who were asked to get the opinion of their groups about a discussion-generating question, which raised doubts about the vaccination strategy. The second episode consisted of following a person’s post expressing his opinion about the senior citizens’ first vaccination day.

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The aim of the third episode of this analysis was to study the first 150 comments that Internet users made on the walls of two prestigious Mexican research-professors: Lorenzo Meyer and Sergio Aguayo. The authors reached the conclusion that, in most cases, people are not interested in discussing or reflecting about certain public interest issues. They have a well-defined political stance that does not allow them to interact or exchange points of view that might contribute to a better informed and more critical community. They observed, at least in the virtual spaces that they studied, that silence can be a major part of—among other headings— the social and political dissatisfaction which the country is going through. Chapter 10 reconstructs the path developed within the volume by proposing a meta-analysis of the practices of infodemic disorder analyzed in the pages of the volume. It proposes a reading of the observed phenomena (from Chaps. 4–9) as sub-units of the macro phenomenon of infodemic disorder (described in Chap. 2), demonstrating the usefulness of the data analysis developed in the volume within the third chapter in order to analyze a social phenomenon such as the emerging one of infodemic disorder. The work process developed throughout the volume follows the abduction model and the communicative practices for the two dimensions for each geographical context (Dimensions = 2, Geographical Contexts = 3; develop DxGC = 6 subunits) outline six attributable communication practices to the infodemic disorder. The developed methodology is recomposed in this last chapter and is that of the nested case study developed for single units in parallel with different techniques and from dissimilar observation points. To reunite the communication practices of the infodemic disorder and develop a meta-­ analysis on them Gevisa La Rocca, Giovanni Boccia Artieri, Marie-Eve Carignan apply an automated procedure, capable of reconstructing the sensemaking developed within the pages of the volume. By focusing on the communication strategies of governments and public health managers and the messages disseminated on social and traditional media in three countries during the Covid-19 pandemic, this book provides a better understanding of the best and less good communication practices adopted to deal with the pandemic and apply health measures and to benchmark communication processes in the three countries, which we will do at the conclusion of this book which proposes a first analysis of information and disinformation processes during the Covid-19 pandemic, from a comparative and international perspective, at a time when the

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international community is still reflecting on the lessons to be learned from this crisis and continues to prepare for the new waves to come. To this end, this book can serve as a point of reference for many other subsequent studies from different areas and countries concerning communication strategies, health communication, disinformation and conspiracy theory as an example. This book will also be very useful for managers and practitioners who want to improve their communication strategies and prepare for future crisis management in public health or other sectors.

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Luhmann, N. (2006). La Confiance. Un mécanisme de réduction de la complexité sociale. Paris, Economica. Milasin, L., & Baert, P. (February 23, 2020). Coronavirus: la Corée en état d’urgence, les voisins de l’Iran se protègent. [Dépêche Agence France-Presse] Le Soleil. Retrieved https://www.lesoleil.com/actualite/monde/coronavirus-­ la-­coree-­en-­etat-­durgence-­les-­voisins-­de-­liran-­se-­protegent-­f121ec07d19f9c8 234d4202c46ea6848 Miller, J. (2020). Psychological, political, and situational factors combine to boost COVID-19 conspiracy theory beliefs. Canadian Journal of Political Science, 1–8. Retrieved https://www.cambridge.org/core/journals/canadian-­journal-­ of-­p olitical-­s cience-­r evue-­c anadienne-­d e-­s cience-­p olitique/ar ticle/ psychological-­political-­and-­situational-­factors-­combine-­to-­boost-­covid19-­ conspiracy-­theory-­beliefs/769693BA993ED5FBE3583803039E27EC Mintzberg, H. (2007). Tracking strategies: Toward a general theory. Oxford University Press. Monnier, A. (2020). COVID-19: De la pandémie à la chasse aux fake news. Recherches et éducations, 10. https://doi.org/10.4000/rechercheseduca tions.9898 OECD. (2020). Maintenir l’accès à l’internet en temps de crise. OECD. Retrieved https://www.oecd.org/coronavirus/policy-­responses/maintenir-­l-­acces-­a-­l­internet-­en-­temps-­de-­crise-­3cd99153/ Office québécois de la langue française (OQLF). (2020). Infodémie. Grand dictionnaire terminologique. Retrieved http://gdt.oqlf.gouv.qc.ca/ficheOqlf. aspx?Id_Fiche=26558108 Olsen, R.  K., Pickard, V., & Westlund, O. (2020). Communal news work: COVID-19 calls for collective funding of journalism. Digital Journalism, 8(5), 673–680. https://doi.org/10.1080/21670811.2020.1763186 Reichstadt, R., & J.  Fourquet (March 28, 2020). L’épidémie dans l’épidémie: Thèses complotistes et COVID-19. Fondation Jean Jaurès, 10. Renard, J. (2015). Les causes de l’adhésion aux théories du complot. Diogène, 249–250(1–2), 107–119. https://doi.org/10.3917/dio.249.0107 Reporters without Borders (RSF). (2020). Censure et attaque. Le journalisme en quarantaine. Retrieved https://rsf.org/fr/censure-­et-­attaques Ricard, J., & Medeiros, J. (2020). Using misinformation as a political weapon: COVID-19 and Bolsonaro in Brazil. The Harvard Kennedy School (HKS) Misinformation Review, 1(2). Roy, J.-H. (2021). Instagram: La une de l’ère mobile. Les Cahiers du journalisme  – Recherches, 2(6), R69–R97. https://doi.org/10.31188/CaJsm.2(6). 2021.R69 Sellnow, D. D., & Sellnow, T. L. (2014). Risk communication: Instructional principles. In T. Thompson (Ed.), Encyclopedia of health communication (Vol. 17, pp. 1181–1184). Sage.

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Smallman, S. C. (2015). Whom do you trust? Doubt and conspiracy theories in the 2009 influenza pandemic. Journal of International and Global Studies, 6(2), Article 1. Retrieved https://digitalcommons.lindenwood.edu/jigs/ vol6/iss2/1 Uscinski, J.  E., Enders, A.  M., Klofstad, C.  A., Seelig, M.  I., Funchion, J.  R., Everett, C., Wuchty, S., Premaratne, K., & Murthi, M.  N. (2020). Why do people believe COVID-19 conspiracy theories? Harvard Kennedy School (HKS) Misinformation Review. https://doi.org/10.37016/mr-­2020-­01. World Health Organization (WHO). (2020a). Conférence sur la sécurité. Munich. Retrieved https://www.who.int/fr/dg/speeches/detail/munich-­security-­ conference World Health Organization (WHO). (2020b). Mise à jour de la stratégie COVID-19. Retrieved https://www.who.int/docs/default-­source/coronaviruse/strategy-­update-­french.pdf

CHAPTER 2

Infodemic Disorder: Covid-19 and Post-truth Giovanni Boccia Artieri

1   Introduction: “We’re Not Just Fighting an Epidemic; We’re Fighting an Infodemic” “We’re not just fighting an epidemic; we’re fighting an infodemic.” With these words, WHO Director General Tedros Adhanom Ghebreyesus defines, at the Munich Security Conference on February 15, 2020, an information dimension that is emerging from the Covid-19 pandemic crisis affecting the world. To speak of infodemics is to emphasize the overabundance of Covid-19-related information circulating in the media ecosystem, which has two consequences: on the one hand, the selection of relevant information is problematic and therefore it is made complex for the public opinion to find the right answers to its questions—which can lead to settle for the first information encountered, thus being driven by selection bias (Prior, 2005); on the other hand, the amount of information that is produced, together with its rapid circulation—often through

G. Boccia Artieri (*) Department of Communication Sciences, Humanities and International Studies, University of Urbino Carlo Bo, Urbino, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. La Rocca et al. (eds.), Infodemic Disorder, https://doi.org/10.1007/978-3-031-13698-6_2

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social media and private chat channels—makes it more complex to distinguish between reliable and unreliable sources, producing the risk of “pollution” of the overall information quality and increasing the risk of coming across false or misleading information. All the more so in a context such as that of a pandemic emergency, in which the need for information is associated with emotional tension and a lack of knowledge on the topic. Moreover, infodemics is part of a more general context of a crisis of legitimacy of the institutions, which is accompanied by a crisis of authority in public communication and the emergence of a condition of information disorder (Wardle & Derakhshan, 2017). This condition has alerted us to the risks of media manipulation of citizens’ attitudes, which are accentuated by the increasingly immediate possibilities of organizing and disseminating information content, and which are reinforced and accelerated by the dynamics of social media and digital spaces. In this sense, the analysis of infodemics acts as a litmus test of the transformation of the information system and of the role those social platforms play in the current dissemination of knowledge, as well as of the risks of pollution of the information environment that are generated by the contemporary form of production, circulation and consumption of information. In this sense, I will address this issue by dividing my contribution into three parts. First, a more complete understanding of infodemics requires exploring the relationship between information and health in our society and the transformations in this relationship due to the characteristics of the contemporary media system. It also requires placing the infodemics in relation to the transformation of public communication, a transformation due, on the one hand, to the crisis of legitimacy of institutional actors— and therefore a crisis of trust also in relation to information sources—and, on the other hand, to the emergence of problems caused by information disorder. Finally, I will try to analyze how infodemics represent a case that allows us to highlight the ambivalent issues related to the theme of information quality today (quality for whom?) and how it is able to highlight the deeper implications of a generalized context of erosion of epistemic authority that connotes an area that we have begun to define as “post-truth.”

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2  The Relationship Between Information and Health in the Connected Society Health constitutes a relevant category in the field of news and contributes to the construction of knowledge that is essential to ensure a vibrant public sphere on the topic (Hodgetts et al., 2008). The construction of this category involves the professional norms and practices of journalism as well as the editorial norms of media and the relationship between media and their audiences. On the one side, journalistic routines tend to focus on lifestyle and individual responsibility and, on the other, on the social and political consequences of policy choices that have to do with the civic dimension of health. The media, for their part, offer frames for interpreting health issues on the agenda by placing them in the public debate, influencing knowledge, attitudes, and behavior (Walsh & Childers, 2016). In this sense, the media simultaneously shape and reflect the public discourse on health (Malone et al., 2000). As the health communication literature of the last decade has highlighted, digital disruption and the evolution of the increasingly hybrid (Chadwick, 2013) and convergent (Jenkins, 2006) media ecosystem have had a significant impact on the way people search for and use health/wellness information in the connected society. As is well known, it is with the advent of Web 2.0 that health information sources have become increasingly numerous and diversified (Bradley et al., 2013). Health, understood as the bio-psycho-social well-being of the person (according to the 1948 WHO declaration), has undergone a significant extension with the pervasiveness of the social and participatory web, becoming a sort of ‘umbrella word,’ as well as a meta-value of contemporary society, around which a plurality of sources, actors, and discourses are developed, which come to life and feed off the new digital communication environments. These are network spaces in which not only information professionals and mainstream media but also individuals and non-profit organizations, institutions, and health and social workers, health centers, pharmaceutical companies, and so on, tend to express their voices, try to gain visibility and be protagonists in the public sphere. In this context, the citizen-patient is recognized as an ‘e-patient’ (Ferguson, 2007), as he or she increasingly searches for and generates information online, shares content, compares experiences and cultivates relationships, participates and expresses opinions and, in some cases, even tends to practice ‘self-help’ (Lupton, 2016). Some scholars have

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highlighted the opportunities and risks associated with these widespread practices: on the one hand, it would lead to greater empowerment of citizens (Cohen, 2010) who, having more information at their disposal and being increasingly skilled in the use of the Internet and social media, would see their expertise on health issues increase. On the other hand, citizens run the risk of coming across incorrect scientific information, of drawing on unreliable sources and may experience difficulties in orientation and selection in the information overload that this context generates. According to a survey conducted by Eurisko in 2016, the use of the Internet for health information is constantly increasing and, above all, the use of social media by citizens to acquire and share information and experiences related to health and well-being is growing. International research has also shown that patients tend to consult the web before a medical visit, with the effect of self-diagnosis, giving rise to the well-known phenomenon referred to as “Dr. Google” or “Dr. Web” (Lee et al., 2015), whereby media information is supplemented by care relationships between different actors in the health system, often linked to economic and business logics, which exploit online information search systems and are confronted with the logic of filtering and visibility of algorithms. While the mass media used to represent health to their audiences through top-down frames and models, the Internet and social media have moved on to a post-representational—that is, constructivist—and bottom­up view of health, in which different voices intersect in the extremely fluid communication flows of the web. The construction of the public discourse on health is therefore affected by the transformations of the media ecosystem and the new forms of representation. The spread of the Internet and social media and their entry into citizens’ media diets, the intertwining of digital and legacy media and the proliferation of user-generated content are all having an impact on the production, circulation, and consumption of health news. Among the consequences, we can, first of all, observe the crisis of legacy media, which have increasingly lost audience, an audience that is less and less ready to pay for news they can find for free online (Brenan, 2020). Traditional publishers of high-quality health news face reduced economic and human resources, as well as competing with new rival sources of information, including social media, blogs, platforms such as Facebook, Twitter, and YouTube, or search engines such as Google towards which audiences, particularly younger ones, turn as an alternative to newspapers, radio, or television (National Academies of Sciences, 2017).

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The speed of the news cycle, with its faster rhythm of production, reduces the time needed for source verification in the publishing system and increases the need for consumption of ever new information content, leading audiences to move easily through the abundance of media channels. This is associated with the rapid circulation of user-generated content that can participate in the growth of misinformation and disinformation phenomena, also through the development of online propaganda strategies (Giglietto et  al., 2020), which also involve an issue such as health. And, more generally, the competitiveness of the news market has made it necessary—to reach audiences in the attention economy—a transformation of health news in an emotional key, through the production of compelling narratives capable of engaging users (Maksimainen, 2017), also with a view to obtaining reactions that can circulate more of those specific contents. For these reasons, it is necessary to consider the level of public engagement with health content within an information ecosystem in which access to information production, circulation, and consumption has become generalized. The current media ecosystem, in the interrelationship between mainstream media and mass access to the Internet, has changed the scale of production and consumption of health-related news, as well as accelerated the speed and level of penetration of consumption of these contents among audiences. In this context, moreover, search engines and social media have taken on the role of information hubs, if not real gatekeepers. The gatekeeping function, which has to do with filtering and controlling the information that achieves social visibility and, therefore, on how this reality is structured (Shoemaker & Vos, 2009), is now confronted with a selective process that takes place in a media environment where non-traditional sources, such as individuals on social media, news portals, or alternative sites, compete for power on the public agenda with institutionalized sources of information (Fletcher & Park, 2017). These new actors apply selective logics that are different from those of traditional gatekeeping agents. They are logics that combine the actions of individuals—in terms of searches, shares, ratings, tagging, and reactions on content—with algorithm-based services, such as search engines and news aggregators that redistribute and channel news online. This is the socio-technological and cultural context in which infodemics is placed and expands, accompanying a major health issue such as the pandemic crisis with a pressing information need.

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3   Infodemics Between Crisis of Trust and Information Disorder In a commentary on SARS entitled “When the Buzz Bites Back,” written in 2003, the Washington Post journalist David J.  Rothkopf coined the word ‘infodemic’ to describe the condition that afflicts those who are overwhelmed by so much information that they suffer from media indigestion. The institutional definition of infodemics is found in the World Health Organization’s Situation Report No. 45 of March 5, 2020, which highlights the more general risk of information pollution during a health emergency: Infodemics are an excessive amount of information about a problem, which makes it difficult to identify a solution. Infodemics can spread misinformation, disinformation and rumors during a health emergency. Infodemics can hamper an effective public health response and create confusion and distrust among people […] During emergencies demand for information is high, there are often many unknowns and people will seek information from sources and individuals and entities they trust.

The question of trust therefore seems to be central both in relation to the need to find information and in relation to the credibility of the information itself: credible information sources and authentic information content seem therefore to be central to the process of correct information, so much so that in the WHO document, trust is seen as a corrective element of information disorder: WHO, through EPI-WIN, has identified such trusted sources and engaged them not only as amplifiers of accurate, timely information, but also as advisers on the kind of information that their constituents need and urgently want to see.

This infocentric approach (Colombo, 2022) assumes that the quality of information is sought by people according to a principle of rationality and that it can produce objective results; it also assumes that the bonds of trust are always positive in the sharing of reliable contents. On the other hand, the case of infodemics shows us, first of all, that the quality of information is also a subjective matter and that it depends on the perception of what is

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to be considered reliable in relation to one’s own convictions and emotional sensibilities. It also shows us that the attribution of trust in information sources follows criteria of selectivity that today involve non-institutional actors, anonymous subjects, homophilic content production channels, and algorithms that personalize search results. Moreover, it shows how the current media system, which is hybrid (Chadwick, 2013) and convergent (Jenkins, 2006), creates an information circuit capable of amplifying the circulation of content faster and with difficulties of centralized control. As Sylvie Briand, director of Infectious Hazards Management at WHO’s Health Emergencies Programme and architect of WHO’s strategy to counter the infodemic risk has argued (Zarocostas, 2020, p. 676): We know that every outbreak will be accompanied by a kind of tsunami of information, but also within this information you always have misinformation, rumors, etc. We know that even in the Middle Ages there was this phenomenon. But the difference now with social media is that this phenomenon is amplified, it goes faster and further, like the viruses that travel with people and go faster and further.

3.1   Information Quality from Opposing Points of View Let us start with the subjectivity relating to the perceived quality of the information. In the evolution of the pandemic crisis, we know how the Covid-19 also acted as a polarizing factor with regard to the issues that gradually arose in relation to the behavior to be adopted and the decisions taken by different countries. From this point of view, we have seen a growing polarization between pro-vax and anti-vax positions. The anti-vax attitude obviously sees the quality of pro-vax information as qualitatively negative, while it looks for good information that clarifies the anti-vax positions. But it is not simply a matter of creating an information landscape characterized by two opposing narratives but also of how these narratives compete in the media and of how specific media environments, such as social media, support the structuring and spreading of these narratives. If we take, therefore, the vaccination issue, we can observe how the anti-vaccination information contents are widely shared online. As evidenced by a Facebook users’ research across countries, continents, and languages (Johnson et al., 2020), the anti-scientist attitude—and therefore a corresponding diffusion of qualitatively toxic information—despite being expressed by smaller clusters and representing ideologically

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marginal opinions, however, appears to have a central positioning in the online network of conversations on vaccines. The content analysis of the clusters highlights how “anti-vaccination clusters offer a wide range of potentially attractive narratives that blend topics such as safety concerns, conspiracy theories and alternative health and medicine, and also now the cause and cure of the Covid-19 virus” (p. 231). 3.2   Information Selection and Infodemics If instead, we observe the dimension of information selection under the lens of the infodemic crisis, we see how selectivity must be understood within the context of information disorder (Wardle & Derakhshan, 2017), characterized by a public communication in which different forms of informational “pollution”: from false content to incorrect correlations, from misinformation (the spread of false information, regardless of whether there is an intent to deceive) to the disinformation (the deliberate spread of false or misleading information with an intent to deceive). These forms must then be associated with the possibilities of media manipulation, coordinated inauthentic behavior, and propaganda (Freelon & Wells, 2020) that various research are beginning to explore showing how there is a significant impact of these forms within digital platforms (Giglietto et al., 2020). A sample analysis of Covid-19 misinformation contents by the Reuters Institute for the Study of Journalism (Brennen et al., 2020), highlights how 88% of the misinformation contents appeared on social media platforms. Alongside the scientific data, the responsibility of social platforms, such as Facebook, Instagram, or Twitter, in the circulation of potentially false and ideologically oriented information content capable of influencing public debate, is also emerging in public opinion in an increasingly significant way. Even individual and group messaging systems, such as Telegram, WhatsApp, or Facebook Messenger, are often vehicles for content that are beyond the control of third parties or public opinion and therefore lend themselves very well to spreading unverified news. While some of these online contents are visible and searchable—therefore also subject to regulatory policies by platforms or third parties, such as fact checkers—others remain “below the radar,” that is, invisible and closed in private chats or groups, with greater difficulty of control and management (Boccia Artieri et al., 2021). According to the OECD (2020) policy brief “Combatting Covid-19 disinformation on online platforms,” the true extent of disinformation is difficult to estimate, and it is also because

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research suggests that people are more likely to share misinformation than they think. Two concomitant processes act in the selectivity processes of this misleading information: on the one hand, the selective biases produced by polarization, on the other, the action of the algorithms. On the first side, we find the effects produced by confirmation bias, that is, by that attitude, typical of human nature, which leads us to confirm a hypothesis through favorable evidence rather than trying to take into consideration contrary evidence. Following the interpretation of those media scholars who argue that those who select the news do so because they already have an opinion on it (Arceneaux & Johnson, 2013), we can say that social platforms, rather than generate polarization, reflect it. Therefore, it is not a question of some conversion of one’s point of view but, rather, of a confirmation actively sought by individuals, currently referred to as confirmation bias. This interpretation, which refers both to studies on selectivity (Bennett & Iyengar, 2008) and to those who consider the audience as an active subject in communication processes, has the merit of bringing the phenomenon of polarization back into a much broader context than the communicative one, giving up the technological shortcut explanation (“it’s the responsibility of the media”) too often used in the study of this complex phenomena. On the second side, we can observe how information recommendation systems based on big data and algorithms are today a fundamental element of selective orientation through which most users browse, select, and consume information online (Beam, 2014). While algorithms facilitate selective processes by allowing information to be filtered, the way they shape the nature and type of information encountered can have a problematic impact on users (Zuiderveen Borghesius et al., 2016). From this point of view, analyzing the Covid-19 infodemics represents an opportunity to observe the ways in which the dissemination of information content shapes digital network structures and how visibility algorithms can also affect them. A study at the University of Warwick in England and at Indiana University Bloomington’s Observatory on Social Media (Menczer & Hills, 2020) shows how even when you want to share or find high-­ quality information, the inability to view all the news in social media feeds inevitably leads to sharing things that are partially or completely false. In practice, the ability of social media algorithms to make some content viral leads to confusing virality (hence the successful exposure of a content) with quality. This cognitive pollution of the selectivity of news is today

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affected by the possible manipulations by the action of bots that are organized to disseminate specific content; in this sense, the proliferation of Covid-19 misinformation by bots, coupled with human susceptibility to believing and sharing misinformation, may well impact the course of the pandemic. (Himelein-Wachowiak et al., 2021). But on the other hand, the action of algorithms is modeled and takes shape in a social and cultural context characterized by a polarization of points of view due to ideological affiliations. A global scale analysis on Twitter (Sacco et al., 2021) highlighted how political polarization significantly affects attitudes related to the pandemic and how conversations on the subject within different cluster-communities are shaped by a small number of actors who generate most of the content and are responsible for most of the related news sources that have circulated. Furthermore, the study shows how the incidence of fake news in some of the community’s conversations is so high that disinformation becomes a key epistemic trait of the community. In this sense, the studies on the online infodemics push us to reflect more deeply on the nature of the so-called fake news. And invite us to avoid interpreting disinformation through a mediacentric vision, certainly taking into consideration the media affordances (such as algorithms) but pushing us to ask ourselves which social and community functions may have misinformation and disinformation, starting from the deepest attitudes of a political, cultural, and emotional nature that we have in front of the news. And pushing us to ask ourselves how infodemics is a constitutive dimension of that phenomenon that we have come to know as ‘post-truth’.

4   Infodemics and Post-Truth On the cultural level, the public debate and research have defined the peculiar context for the development of information contents and post-­ factual and post-reality social orientations as a context of post-truth (Maddalena & Gili, 2020). It is a condition of political and civil culture that sees the emergence of appeals and communicative clashes largely based on the emotional dimension, poorly connected to the analysis of the facts and concrete evidence, in such a way that any attempt to disprove the affirmations based on data analysis or on fact-checking practices is systematically ignored. In this sense, the pandemic experience revealed the general shift towards a post-truth disposition in contemporary social life (Shelton, 2020).

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The fact that misinformation and disinformation news on Covid-19 become a relevant topic to be dealt with publicly, and on which to focus attention, highlights a specific problem: that with post-truth we are facing a cultural clash. As Cory Doctorow (2017) explains, “we’re not living through a crisis about what is true, we’re living through a crisis about how we know whether something is true. We’re not disagreeing about facts, we’re disagreeing about epistemology.” Post-truth is the declination of a cultural context different from that which characterizes the traditional forms of contestation and protest as well as that in which a systematic falsification of reality is carried out. And this is because, on the one hand, the principle of truth is relegated to a secondary position with respect to the emotional dimension and, on the other, because truth becomes a subject of a deeper cultural clash between elites, communities, and different worldviews. In this sense, even the propagation of a ‘fake news’ has not so much to do with the reality principle as with support for a different belonging; that is, it can serve as an example of one’s own positions. A post on Facebook that not only represents one’s own positions but presents them in a clear and unequivocal way—for example, a meme denouncing the risks of the vaccine—does not require verification and even if there is an awareness of its falsity, it does not matter: its sharing has an expressive function with respect, for example, to the anger one feels for a specific event, whether it is having to wear masks, getting vaccinated, or having a green pass to enter a restaurant. Sharing content can therefore represent an act of adherence to a worldview or to a political or social group, it constitutes an affirmation of identity in public. These are behaviors useful to mark differences with respect to other social groups, which are based on a partisan attitude that one can have towards the truth itself—as when the subjective perception of the presence of immigrants by the population does not correspond to the official statistics of a country. Post-truth therefore has to do with a generalized crisis of confidence in politics as well as in the media, in intermediate social bodies as well as in intellectual elites. The Internet becomes, in this context, a useful expressive tool to destabilize the communicative structures and worldviews of others, in a continuous ambivalence between unity and conflict, between rationality and affectivity (Phillips & Milner, 2017). The emotional side— with references to direct experience that connotes much of the content of politics in the post-truth era—is not in contradiction with a rational dimension: affectivity and rationality should not be thought of as

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opposing poles or binary alternatives, but in their entanglement and referral to each other. People rationally lend their voices (by producing and sharing content online) to affectively tune in to other people (Papacharissi, 2015), and their participation produces an emotional experience capable of reflecting on their thinking. The antagonistic discourse is amplified in a cacophony of voices, not always clearly ascribable to a clear and defined position, which contributes to raising the tension of public discourse, to propagating a specific sentiment, through ironic or vulgar modes, manipulating original contents by giving them the form of fakes, constructing hoaxes, through Facebook pages with a satirical appearance, and so on. The affordances of platforms—that is, the technical characteristics together with the forms of interpretation and use—their policies, and the impulsive behavior of users allow the propagation and visibility of specific contents that function as markers of their taste and become part of the online self-narrative.

5  Conclusions In this chapter, I have used the theme of infodemics, as a crisis due to the overabundance of information and the difficulty of selecting quality information content, as a territory for exploring deeper dynamics that have to do (a) with the relationship between information and health; (b) with the transformation of knowledge modalities in the intertwining of the social system and a media ecosystem that sees social platforms as increasingly central; and (c) with the problematic consequences that the information disorder present in pandemic information can create. In this sense, I have highlighted how the use of the Internet for information on health issues has grown, and how social media in particular are now central to people when it comes to both selecting information on health and sharing their experiences on the topic. The information circuits between mainstream and non-mainstream media have also changed, reconfiguring the media ecosystem which sees a generalized crisis of trust in legacy media and their editorial systems, an acceleration of news cycles and an increasingly central gatekeeper function on the part of social platforms. The generalized crisis of trust also affects the legitimacy of institutional actors, including information sources, and feeds a state of infodemic information disorder that undermines the quality of information itself through the production, circulation, and consumption of misinformation

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and disinformation. But I have also highlighted how ‘infodemic disorder’ is a breeding ground for an epistemological struggle that has deeper causes than the skirmishes we see represented in the media, for example, between pro- and anti-vax. Certainly, the infodemics is a context in which the risk of manipulation is high and in which the mechanisms linked to the visibility algorithms of social media can make the virality of a content be mistaken for its quality. But, as I have argued, at a deeper level, the existence and circulation of these contents is an indicator of a cultural clash over different worldviews and has to do with deeper reasons than the contingent ones surrounding the pandemic. This is a context that I have reconstructed by appealing to the concept of post-truth, which refers to an erosion of epistemic authority and an epistemological conflict between ‘truths’ that are carriers of different worldviews. The growth of difference in values and attitudes—think of that between globalists and sovereignists—and the worsening of social conflicts, produce cultural universes that are not only distinct but that conflict with each other. And the existence of these cultural universes is a challenge to the validity and legitimacy of others. The social reasons for this conflict are well explained by Robert K. Merton when he states that: “The coexistence of these conflicting perspectives and interpretations within the same society leads to an active and reciprocal distrust between groups. Within a context of distrust, one no longer inquiry into the content of beliefs and assertions to determine whether they are valid or not, one no longer confronts the assertions with relevant evidence, but introduces an entirely new question: how does it happen that these views are maintained?” (Merton, 1996, p. 205). Despite the amount of data and information, our experience and response to the pandemic is therefore also very much shaped by a tendency to put ‘truth’ on the back burner. Obviously, the production and interpretation of information is a fundamentally (inter)subjective and power-laden process, shaped by many different social, cultural, political, and economic considerations. But the pandemic was an event that showed how, in our society, the polarization between points of view has deeper roots, pointing to an epistemological clash that will be an underlying tension in our social living. The cultural and technological conditions of post-­ truth, which the Covid-19 infodemic has made even more evident, are thus rooted in deep social and communicative transformations whose surface we have only just begun to explore. And which move at the margins of public discourse in the media, only to explode, unpredictably, onto the scene on certain occasions, such as that of a pandemic.

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References Arceneaux, K., & Johnson, M. (2013). Changing minds or changing channels?: Partisan news in an age of choice. University of Chicago Press. Beam, M. A. (2014). Automating the news: How personalized news recommender system design choices impact news reception. Communication Research, 41(8), 1019–1041. Bennett, W. L., & Iyengar, S. (2008). A new era of minimal effects? The changing foundations of political communication. Journal of Communication, 58(4), 707–731. Boccia Artieri, G., Brilli, S., & Zurovac, E. (2021). Below the radar: Private groups, locked platforms, and ephemeral content—Introduction to the special issue. Social Media+ Society, 7(1), 1–7. https://doi.org/10.1177/ 2056305121988930. Bradley, W., Sparks, L., & O’Hair, D. (2013). Health communication in 21st century. Wiley. Brenan, M. (2020). Americans remain distrustful of mass media. News Gallup. https://news.gallup.com/poll/321116/americans-­r emain-­d istrustful-­ massmedia.aspx Brennen, J.  S., Simon, F.  M., Howard, P.  N., & Nielsen, R.  K. (2020). Types, sources, and claims of COVID-19 misinformation. Doctoral dissertation, University of Oxford. Chadwick, A. (2013). The hybrid media system: Power and politics. Oxford University Press. Cohen, E. (2010). The empowered patient: How to get the right diagnosis, buy the cheapest drugs, beat your insurance company, and get the best medical care every time. Ballantine Trade Paperback Original. Colombo, F. (2022). An ecological approach: The infodemic, pandemic, and COVID-19. In K. Kopecka-Piech & B. Łódzki (Eds.), The Covid-19 pandemic as a challenge for media and communication studies (pp. 35–48). London. Doctorow, C. (2017). Three kinds of propaganda, and what to do about them. https://boingboing.net/2017/02/25/counternarratives-­not-­fact-­che.html Ferguson, T. (2007). e-Patients: How they can help us heal healthcare. White Paper. San Francisco, Society of Participatory Medicine. https://whatsthefix.info/ w p -­c o n t e n t / u p l o a d s / 2 0 1 8 / 0 5 / e -­P a t i e n t -­W h i t e -­P a p e r -­w i t h 2013-­Afterword-­SPM-­logo.pdf. Fletcher, R., & Park, S. (2017). The impact of trust in the news media on online news consumption and participation. Digital Journalism, 5(10), 1–19. Freelon, D., & Wells, C. (2020). Disinformation as political communication. Political Communication, 37(2), 145–156.

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CHAPTER 3

A Review of Some Covid-19 Pandemic Numbers in European Union, Canada, and Mexico Fabio Aiello and Giovanni Boscaino

1   Introduction Coronavirus disease, more simply named as Covid-19, is an infectious disease caused by the SARS-CoV-2 virus. The first official report of the presence of SARS-CoV-2 infection was made by the Chinese health authorities on December 31, 2019, to notify the existence of an outbreak of pneumonia cases of unknown etiology, in Wuhan city (Hubei Province, China). On January 9, 2020, the China CDC (Centre for Disease Control and Prevention) disclosed that it had identified the etiological cause of the outbreak in a new coronavirus, initially named 2019-nCoV, which, on

F. Aiello (*) Kore University of Enna, Enna, Italy e-mail: [email protected] G. Boscaino University of Palermo, Palermo, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. La Rocca et al. (eds.), Infodemic Disorder, https://doi.org/10.1007/978-3-031-13698-6_3

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February 11, 2020, the World Health Organization (WHO) definitively named Covid-19. On March 11, 2020, after assessing the levels of severity, rate of infection transmission, and global spread, the WHO declared that the Covid-19 outbreak should be considered a pandemic. Most individuals with Covid-19 disease experienced mild, at most moderate symptoms, very similar to those of a common flu. However, from its earliest stages of spread, Covid-19 disease has been distinguished by its speed of transmission and the severity of its consequences. In fact, the numbers of both individuals hospitalized in Intensive Care Units (ICU) and deaths due to the disease have been high. Wherever in the world Covid-19 disease has spread, local health authorities have identified three main parameters to monitor the transmission of the disease and its consequences, these are: the number of new cases, that is, the number of subjects positive to the disease (referred to as the incidence (Fletcher & Fletcher, 2005, p. 60), to assess the speed of the disease infection; the number of subjects hospitalized in Intensive Care Unit (ICU), to handle the pressure on the health care system; and, finally, the number of deaths due to the Covid-19 disease (i.e., its mortality), to measure its seriousness. As it is well known, infection-related mortality and the risk of admission to the ICU are two events whose high frequency has characterized the spread of the infection over time. Reference will be made to the three information mentioned above, which are universally shared and used to monitor the spread of the infection, and its effects on the population, over time. The aim of this chapter is twofold. First, descriptive: to depict the evolution of the Covid-19 disease infection, in approximately the first year of its appearance, in each of the three different continental areas of the globe: Canada, the European Union, and, finally, Mexico. Then, comparative: to contrast trends in the three geographic areas, jointly taken, over time. These areas are three confederations born at different times through a process of federal union: Mexico in 1857, then Canada in 1867, and finally, the European Union, in 1999. Descriptive analyses of trends over time for each of the three pieces of information mentioned above will be presented below. The data employed were taken from Johns Hopkins University and Medicine,1 and 1  Johns Hopkins University—University of Medicine (2021), https://coronavirus.jhu. edu/ (2021). Accessed 01 May 2021.

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they are based on information released by the local competent official health authorities, in each of the three nations. The search for useful information to reach our objectives has required a considerable commitment: the quantity of sources and information available on the web is boundless, but not always reliable, or more simply, not suitable because it is not homogeneous with respect to essential characteristics for use. The “criterion” of the homogeneity of the data, with respect to the modalities of collection and communication that has guided us in the research of the information, is based on the need to compare the three nations with respect to the times and the ways in which they have been affected by the waves of infection of the Covid-19 disease. Then, the need to have a reliable source, from which to draw homogeneous and therefore comparable data, has determined, if not forced, the final choice of the source. The aspect of homogeneity was the reference both to trace the data of the three nations, but also to define the dataset for the European Union. Care was needed to define this latter dataset, as the collection and communication of information for the European Union is not centralized but is the responsibility of the individual member states. Therefore, starting from these, it was necessary to proceed by successive aggregations. Given these premises, the information (ISO 8601 base format) used in this work expresses three indicators monitored to manage the transmission of the infection, which are 1. The number of new virus-positive individuals (here named as new cases). 2. The number of deaths due to Covid-19 disease (here named as deaths). 3. The number of people admitted to the ICU (here named as ICU admissions). The information released by the source are referred to daily surveys; here, instead, they have been aggregated to weekly level to make them more manageable and consistent with what is done by most local health authorities. Then, we first collected the daily information and afterward we aggregated it on a weekly basis. The beginning of the observation interval is set to January 24, 2020 (the date of the first official positive case

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of Covid-19  in the European Union), while the end is set to May 13, 2021, thus defining 68 weeks of observation. Since our objective is twofold, in the analysis, the information in question is used in two different forms: first, in absolute terms, for the descriptive analysis; then, in standardized form (expressed per million people), for the comparative analysis. In addition, two measures derived from the information we have will be employed: the index of weekly percent variation, for descriptive purposes, and the effective reproduction number, Rt, estimated by a method described later, for comparative ones. The index of weekly percentage variation expresses the magnitude of the variation observed in each week, compared to the previous one, over the 68-week interval, while the effective reproduction number, Rt, describes the spread of an infectious disease within a population that is not fully susceptible to the pathogen. No analysis of the information in question, with respect to risk factors such as gender and age, is presented here, since at the time of the data search, it was not possible to find homogeneous data with respect to both the observation interval and the methods of detection, both between and within the geographical areas under examination. The chapter is organized as follows: the first section is devoted to a descriptive analysis of the spread of Covid-19 disease infection, with a paragraph for each geographical area and a subsection for each piece of information analyzed. The second section is dedicated to the comparative analysis of the spread of Covid-19 disease infection in the three geographic areas, with a paragraph for each piece of information analyzed. Finally, the conclusions section contains some reflections on what emerged during the previous sections.

2   Waves of Covid-19 Infection in Canada, the EU, and Mexico This section presents descriptive analyses conducted on the information collected to manage the different waves of Covid-19 infection that occurred during the 68-weeks interval of observation, measured in terms of weekly new Covid-19 cases, deaths due to Covid-19, and, finally, ICU admissions. A paragraph is devoted to each of the three geographic areas in question; a sub-paragraph is devoted to each of the information analyzed.

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3  Canada In Canada, the estimated population2 in 2020 was about 38 million, making it the least populated geographic area among those considered here. Public Health Agency of Canada dated the first report of Covid-19 positive cases to January 26, 2020, the first death due to Covid-19 was recorded on March 9, 2020 (week 7), about six weeks after the first positive case, and the first ICU admission was recorded on March 13, 2020 (week 8), about seven weeks after the first Covid-19 positive cases. In Table  3.1, there are some statistics of the information collected for Canada. The three pieces of information under examination show different behaviors with respect to the waves over time. In fact, the number of new cases and the number of admissions to the ICU increase, both reaching their maximum value at the peak of the last wave (61,030 and 10,180, respectively). On the other hand, deaths decrease, reaching their maximum value at the peak of the first wave (equal to 1329). In Canada, during the whole 68-week interval, there were

Table 3.1  Summary statistics of new cases, deaths, ICU admission, by wave, in Canada Waves

Statistics

New Cases

Deaths

ICU Adm.

I

Peak M/Y Week Peak M/Y Week Peak M/Y Week Total

12,490 Apr/20 13 55,284 Jan/21 50 61,030 Apr/21 64 1,314,420

1,329 Apr/20 14 1,020 Jan/21 52 355 Apr/21 66 24,755

3,920 Apr/20 12 6,116 Jan/21 51 10,180 May/21 67 192,176

II

III

Overall

 Statistics Canada (2021). https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1710000901&cubeTimeFr a m e . s t a r t M o n t h = 0 1 & c u b e T i m e F r a m e . s t a r t Ye a r = 2 0 2 0 & c u b e T i m e F r a m e . endMonth=10&cubeTimeFrame.endYear=2020&r efer encePeriods=2020010 1%2C20201001 (2021). Accessed 02 May 2021. 2

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–– Three waves. –– 1,314,420 Covid-19-positive subjects (approximately 3.5% of the population). –– 24,755 deaths due to Covid-19 (1.9% of all positive subjects). –– 192,176 ICU admissions due to Covid-19 (14.6% of all positive subjects). The trend over time for each information is described below. 3.1   Weekly New Cases Figure 3.1 shows the weekly trend of the new cases of Covid-19 in Canada in the 68-week interval. Two distinct phases of infection expansion are distinctly observed, the first considerably less in extent and intensity. The first phase takes shape with the wave in the spring of 2020 (weeks 8–13), the second one, by two waves: the first in August 2020–January 2021 (weeks 31–50), and the second in February–April 2021 (weeks 59–64). The first wave is far from the last two waves, that instead are very close between them: in fact, the peaks of the first two waves are thirty-seven weeks apart and those of the last two waves, on the other hand, are only fourteen weeks apart. Moreover, there is considerable difference between the first wave and the others, both in terms of intensity and extent. Finally, the third wave is the one of highest intensity. In more details, it can be seen that

Fig. 3.1  Weekly trend in the number of new cases of Covid-19 in Canada

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i. The first wave begins in March 2020 (week 8), when the weekly number of positives increases from 683 to 12,490 in late April 2020 (week 13), and then declines and remains around 2000–3000 cases between June and August 2020 (weeks 21–30), ii. The second wave is the largest one, in terms of the number of weeks. It begins in late August 2020 (week 31), when the number of cases increases from 3211 to 55,284 in January 2021 (week 50). In the successive weeks it quickly decreases to approximately 21,000 cases per week. iii. The third wave is the quickest one to reach its peak and it starts at the beginning of March 2021 (week 59), when the weekly number of new cases increases from 21,524 to 61,030, the highest value over time, in April 2021 (week 64). Figure 3.2 shows the weekly percentage variations of the number of new cases in Canada, over time. This is the evolution of a cumulative process over time, in which the numerous and consistent increases recorded in the weeks of the first wave are followed, in subsequent weeks, by reduced decreases, both in number and in intensity. It can be observed that from the beginning of the first wave (around the fifth week), and for the following 63 weeks, the number of recorded positive variations (39) is 56% higher than the number of negative ones (25, which are rarely of significant size). For this reason, the increases recorded in the last two waves appear relatively less large than those

Fig. 3.2  Weekly percentage variations in the number of new cases of Covid-19 in Canada

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recorded in the first wave. These are increments based on values that have almost always grown over time, and thus have reached considerable levels. Finally, the highest increase is recorded between the seventh and eighth weeks, precisely at the beginning of the first wave, when it goes from 80 new cases to 683 (+754%). 3.2   Weekly Deaths Figure 3.3 shows the weekly trend of the deaths due to Covid-19  in Canada in the 68-week observation period. Here again, the waves are essentially three: the first one in the spring of 2020, the second one in autumn 2020, and the third one, numerically much smaller than the first, in the spring of 2021. It is worth noting that the number of deaths due to the first wave is significantly higher than that of the second wave, even though the number of infections in the first wave was significantly lower than in the second wave. In more details, it can be seen that i. The first wave begins in late March 2020 (week 9), two weeks after the first wave of new cases, when the number of deaths increases from 46 to 1329 in late April 2020 (week 14), reaching the highest value of the 68-week interval, then it quickly declines. ii. The second wave starts in late September 2020 (week 36), five weeks after the second wave of new cases, when the number of deaths increases from 82 to 1020, in January 2021 (week 52).

Fig. 3.3  Weekly trend in the number of deaths due to Covid-19 in Canada

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iii. The third wave is the shortest one and it starts in April 2020 (week 64), five weeks after the third wave of new cases, when, in two weeks, the number of deaths increases from 286 to 355 (week 66). Although it appears to be decreasing, nothing can be said about its subsequent trend, since it is right at the end of the 68-week interval. It looks more like the tail of the second wave, rather than a wave. Figure 3.4 shows the weekly percentage variations of the number of deaths due to Covid-19 in Canada over time. Similar considerations to those expressed for the number of new cases can be made for the weekly percentage variations in the number of deaths. The first positive change (+900%, this may seem like misleading information) is at the eighth week (first wave), when deaths range from 1, in the seventh week, to 10. In the weeks that followed, there were still consistent positive increases, albeit in a more limited manner, as the absolute values recorded increased. Over the next 61  weeks, increases (32) outnumber decreases (27) by 18%. Finally, a noteworthy increase is recorded from the thirty-sixth (second wave) to the thirty-seventh week, when the number of deaths rises from 82 to 247 (+201%). 3.3   Weekly ICU Admissions Figure 3.5 shows the trend of the weekly ICU admissions due to Covid-19, in Canada, in the 68-week interval. Again, there are three distinct waves

Fig. 3.4  Weekly percentage variations in the number of deaths due to Covid-19 in Canada

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Fig. 3.5  Weekly trend in the number of ICU admissions due to Covid-19 in Canada

that are essentially contemporaneous with the new cases and have similar characteristics to them: in fact, only 16 weeks elapse between the last two peaks, compared to 39 weeks between the first two peaks. It is interesting to note that although the last two waves of infections appear to be quite similar in the number of new cases per week, the number of weekly ICU admissions is significantly lower in the second wave than in the third one. Finally, from December 2020 (week 46) onward, the number of weekly ICU admissions remains mostly above the levels of the first wave peak. In more details, it can be seen that i. The first wave is numerically the least significant, but it has the highest growth rate, since, in a few weeks, it achieves its maximum value, going from 43 admissions in March 13–16, 2020 (week 8) to 3920, in April 10–16, 2020 (week 12). ii. The second wave is the largest and it is observed from about August–September 2020 (week 32) to February 2021 (week 58). It has an intermediate numerical significance compared to the other two. Its peak is at 6116 ICU admissions recorded in January 2021 (week 51). iii. The third wave, or at least what it appears to be, as it begins in March 2021 (week 60), has a high growth rate and, although it cannot be said that the 10,180 new ICU admissions recorded in May 2021 (week 67) are really the peak of the third wave, they are certainly the highest value recorded in the entire interval considered.

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Figure 3.6 shows the weekly percentage variations of the number of ICU admissions due to Covid-19 in Canada over time. The trend of this variation index is like those of the previous homologous indices. In fact, the highest relative increases are registered in correspondence with the first wave of infection, that is, from the eighth (43) to the ninth week (352), when the number of ICU admissions increases enormously (+718.6%). In the weeks that followed, there were still consistent positive increases, albeit in a more limited manner, as the absolute values recorded increased. Over the next 60  weeks, increases (35) outnumber decreases (25) by 40%. Finally, a noteworthy increase is recorded from the thirty-­ sixth (second wave) to the thirty-seventh week, when the number of deaths rises from 82 to 247 (+201%).

4  The European Union In the European Union, the estimated population3 in 2020 was approximately 447 million, making it the most populated geographic area among those considered here. The first confirmed case of Covid-19  in the European Union was reported in France on January 24, 2020, and subsequently spread widely across the continent. By March 17, 2020, every country in Europe had confirmed a case, and all had reported at least one

Fig. 3.6  Weekly percentage variations in the number of ICU admissions due to Covid-19 in Canada  Eurostat. Data Browser (2021). https://ec.europa.eu/eurostat/databrowser/view/TPS00001/bookmark/table?lang=e n&bookmarkId=c0aa2b16-607c-4429-abb3-a4c8d74f7d1e (2021). Accessed 02 May 2021 3

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death. In France were recorded both the first ICU admission, on February 2, 2020 (week 2), and the first death due to Covid-19, on February 15, 2020 (week 4). The first official act of the European Union was (January 28, 2020) to activate the EU civil protection mechanism to provide consular support to EU citizens in Wuhan, China, for repatriation. In Table  3.2, there are some statistics of information collected for the European Union. The three pieces of information under examination show three different behaviors with respect to the waves, over time. In fact, the number of new cases seesaws, reaching the maximum value at the peak of the second wave (1,424,178); deaths gradually decrease, from 21,952  in the first wave to 14,787 in the third wave; and, finally, ICU admissions increase, reaching the maximum value at the peak of the third wave (144,538). In the European Union, during the whole 68-week interval, there were –– Three waves. –– 29,148,227 Covid-19-positive subjects (approximately 6.5% of the population). –– 641,876 deaths due to Covid-19 (2.2% of all positive subjects). –– 4,574,475 ICU admissions due to Covid-19 (15.7% of all positive subjects). The trends over time for each item of information are described below.

Table 3.2  Summary statistics of new cases, deaths, ICU admission, by wave, in the European Union Waves

Statistics

New Cases

Deaths

ICU Adm.

I

Peak M/Y Week Peak M/Y Week Peak M/Y Week Total

208,604 Apr/20 12 1,424,178 Nov/20 41 979,368 Mar/21 62 29,148,227

21,952 Apr/20 11 21,895 Dec/20 47 14,787 Mar/21 62 641,876

121,956 Apr/20 11 139,453 Nov/20 43 144,538 May/21 64 4,614,445

II

III

Overall

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4.1   Weekly New Cases Figure 3.7 shows the weekly trend of the new cases of Covid-19 in the European Union in the 68-week interval. Two distinct phases of infection expansion are distinctly observed, the first considerably less in extent and intensity. The first phase takes shape with the wave of March–May 2020 (weeks 7–12), the second, by two waves, that of July–November 2020 (weeks 26–41), the most dramatic of all, followed by that of February– April 2021 (weeks 57–62). Huge difference, especially between the first and second waves, in terms of the order of magnitude reached by the weekly number of new cases, which increases from hundreds of thousands in the first wave, to over a million in the second. The third wave has a lower intensity than the second, but still dramatic, especially with respect to the first one. In more details, it can be seen that i. The first wave begins in late February 2020 (week 6), when the weekly number of positives increases from 4618 to 208,604 in mid-­ April 2020 (week 12), and then declines and remains around 30,000 cases between May and July 2020 (weeks 17–25). ii. The second wave is the most dramatic one, both in terms of intensity, that is, the number of new cases per week, and in terms extent, that is, the number of weeks. It begins in late July 2020 (week 26), when the number of cases increases exponentially from 40,204 to 1,424,178  in November 2020 (week 41), the highest value over

Fig. 3.7  Weekly trend in the number of new cases of Covid-19  in the European Union

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time. In the weeks immediately following, values decrease dramatically, then there are some fluctuations around 900,000–800,000 new cases per week, and, after 15 weeks (mid-February 2021), the weekly number of new cases has practically halved. iii. The third wave begins at the end of February (week 57) when the weekly number of new cases starts to rise again from 652,652 to 979,368 cases at the end of March 2021 (week 62). Then the weekly values decrease rapidly, to 400,000 cases at the end of the observation interval. Figure 3.8 shows the weekly percentage variations of the number of new cases of Covid-19 in the European Union, over time. Here a premise must be made: the first increase in the number of new cases in the European Union is recorded in the fifth week, with respect to the fourth week (737 versus 1, respectively). The percentage increase (73,600%) is so big that all other variations in the graphical representation become incomprehensible and insignificant. For this reason, in the figure this increase is set at 530, the maximum among the observed increases. Given this premise, however, it can be said that even in this case the largest weekly percentage increases are those registered at the first wave. It can be also observed that from the beginning of the first wave (around the fifth week), and for the following 64 weeks, the number of recorded positive variations (38) is 46% higher than the number of negative ones (26).

Fig. 3.8  Weekly percentage variations in the number of new cases of Covid-19, in the European Union

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4.2   Weekly Deaths Figure 3.9 shows the weekly trend of the deaths due to Covid-19 in the European Union in the 68-week interval. Once again, the pattern of deaths over time looks like that of the weekly number of new cases, that is, it presents three distinct waves. It is worth noting that the number of deaths due to the first wave is the same as that of the second wave, even though the number of infections in the first wave was lower than in the second wave. This is probably due to the different composition of the two cohorts of infected people: in fact, it is known that the first wave affected more elderly and/or frail individuals, in whom the presence of comorbidities is more frequent, and among whom mortality was very high. The subsequent waves, on the other hand, have involved younger subjects, more resistant to the pitfalls of the disease and to extreme medical treatments. An analysis of the cohorts’ composition of infected individuals would be useful, but is beyond the scope of this paper. In more detail, it can be seen that i. The first wave begins in March 2020 (week 6), one week after the first wave of new cases, when the number of deaths increases from 139 to 21,952 in April 2020 (week 11), reaching one of the higher values of the 68-week interval, then it quickly declines. ii. The second wave starts in late August 2020 (week 30), three weeks after the second wave of new cases, when the number of deaths increases from 1063 to 21,957, in January 2021 (week 51). It is

Fig. 3.9  Weekly trend in the number of deaths due to Covid-19  in the European Union

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worth noting that for thirteen consecutive weeks, that is, between November 2020 and February 2021, the number of deaths remained around 20,000 per week. iii. The third wave starts in mid-March 2021 (week 61), four weeks after the third wave of new cases, when in two weeks the number of deaths increases from 14,111 to 14,787 (week 62), and only after the sixty-fourth week does it decline. Figure 3.10 shows the weekly percentage variations of the number of deaths due to Covid-19 in the European Union, over time. Again, the first increase in the number of deaths (1700%) due to Covid-19 is observed in the fifth week, with 18 deaths compared with the one in the previous week. For the reasons explained above, in the figure its value is set at 680, the maximum among the observed increases. Similar considerations to those expressed for the number of new cases can be made for the weekly percentage variations in the number of deaths. In fact, it can be observed that the largest increases are concentrated in the first wave. Two other noteworthy increases can be seen in the twenty-­ second week (+65.5%) and the forty-first week (+77.4%). Here the number of positive variations is only 13% greater than the number of negative variations.

Fig. 3.10  Weekly percentage variations in the number of deaths due to Covid-19 in the European Union

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4.3   Weekly ICU Admissions Figure 3.11 shows the trend of the weekly ICU admissions due to Covid-19, in the European Union in the 68-week interval. Here, again, we observe two distinct phases of growth in the weekly number of ICU admissions, resulting in three peaks that grow over time and almost perfectly coincide (or at most two weeks late) with the peaks in new cases. The three peaks stem from the increases observed in March–April 2020 (weeks 6–11), August–November 2020 (weeks 31–43), and, finally, March–April 2021 (weeks 58–64), and are all values above 120,000 units. It is also interesting to note that between November 2020 (week 41) and April 2021 (week 66), that is, for twenty-six consecutive weeks, the number of weekly ICU admissions remained consistently above 100,000. In more details, it can be seen that i. The first wave starts in March 2020 (week 6), when the weekly number of ICU admission increases from 1486 to 121,956 in April 2020 (week 11), and then it quickly declines. It has the highest growth rate, since in five weeks it achieves its maximum value. ii. The second wave starts in late August 2020 (week 31), when the weekly number of ICU admission increases from 13,722 to 139,453 in November 2020 (week 43). Subsequently, it decreases slowly, stopping its descent on values of about 120,000 units and over.

Fig. 3.11  Weekly trend in the number of new ICU admissions in the European Union

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iii. The third wave begins in March 2021 (week 58), when the weekly number of ICU admissions increases from 112,300 to 144,538 in April 2021 (week 64), reaching the maximum value of the whole of the 68-week interval. It is worth noting that the highest values (equal to at least 140,000) of ICU admissions are observed around this peak (weeks 63–65). Figure 3.12 shows the weekly percentage variations of the number of ICU admissions due to Covid-19 in the European Union over time. Again, the first increase in the number of ICU admissions (16,100%) is observed in the fifth week, with 162 deaths compared with the one in the previous one. For the reasons explained above, in the figure its value is set at 820, the maximum among the observed increases. And, as in previous cases, the greatest increases are concentrated in the first wave and the ratio between the number of positive and negative increases is in favor of the former (+28.6%).

Fig. 3.12  Weekly percentage variations in the number of ICU admissions due to Covid-19 in the European Union

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5   Mexico In Mexico, the estimated population4 in 2020 was about 126 million, making it the second most populated geographic area among the three considered here. The National Council of Science and Technology (CONACYT) reported the first two cases of COVID-19 in mid-January 2020  in the states of Nayarit and Tabasco, with one case per state,5 although officially, the onset of Covid-19 infection in Mexico is dated February 28, 2020. The first death due to Covid-19 was recorded on March 19, 2020 (seventh week), about seven weeks after the first positive case. For Mexico, at the time of the data search, information on new admissions to the ICU could not be tracked. Therefore, the analyses presented below refer only to weekly new cases and deaths. In Table  3.3, there are some statistics of the information collected for Mexico. The two waves of infection that hit Mexico almost tripled the number of new cases, from 46,671 to 122,914, and almost doubled the number of deaths, from 5313 to 9994. In Mexico, during the whole 68-week interval, there were –– Two waves. –– 2,371,483 Covid-19-positive subjects (approximately 1.9% of the population). –– 219,590 deaths from Covid-19 (9.3% of all positive subjects). Table 3.3  Summary statistics of new cases, deaths, ICU admission, by wave, in Mexico Waves

Statistics

New Cases

Deaths

I

Peak M/Y Week Peak M/Y Week Total

46,671 Jul/20 26 122,914 Jan/21 52 2,371,483

5,313 Jun/20 22 9,994 Febr/21 55 219,590

II

Overall

4  INEGI, (2021). https://en.www.inegi.org.mx/temas/estructura/. Accessed 02 May 2021. 5  Covid-19 México, (2021). https://datos.covid-19.conacyt.mx. Accessed 03 May 2021.

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The trends in the individual pieces of information under consideration here are analyzed in more detail below. 5.1   Weekly New Cases Figure 3.13 shows the weekly trend of the new cases of Covid-19  in Mexico in the 68-week interval. Two waves can be distinguished, and between them a peak, both of noticeable extent. From June 2020 (week 20) to March 2021 (week 60), the weekly number of new cases is never less than 30,000, and from late November 2020 (week 44) to mid-­ February 2021 (week 56) it always exceeds 50,000, reaching its maximum value of 122,914 in mid-January 2021 (week 52). In more details, it can be seen that i. The first wave begins in mid-March 2020 (week 8), when the number of positives increases from 152 to 46,671  in mid-July 2020 (week 26), and then declines and remains around 31,000 cases between September and October 2020 (weeks 33–36). ii. The second wave is much more dramatic than the first in terms of incidence and temporal extent. It begins in late fall 2020 (week 44), when it rises from 59,051 to 122,914 new cases in mid-January 2021 (week 52). It then declines rapidly thereafter, but remains above 40,000 new cases for another six weeks (March 2021).

Fig. 3.13  Weekly trend in the number of new cases of Covid-19 in Mexico

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As mentioned above, it is worth noting that there is an intermediate peak that looks more like an outlier in incidence (56,173 new cases in week thirty-seven) compared to values in adjacent weeks (32,858 and 30,422 new cases, in weeks thirty-sixth and thirty-eighth, respectively), rather than a true wave. This could be due to a collection error made in previous weeks. Figure 3.14 shows the weekly percentage variations of the number of new cases of Covid-19 in Mexico, over time. Again, the first increase in the number of new cases (2071.4%) is observed in the eighth week, with 152 deaths compared to 7 in the previous week. For the reasons explained above, in the figure, its value is set at 200, the maximum among the observed increases. As in previous cases, the greatest increases are concentrated in the first wave, but unlike previous cases, for the first time here, we observe substantial increases even in the weeks following those of the first wave. For example, the sudden surge observed at week 37 (+71%, compared to the previous week), and the sequence of substantial increases observed at the second wave, which, in Mexico, begins at week 44 (+113%, compared to the previous week). Finally, starting from the eighth week, in the following 60  weeks, the number of recorded positive variations (32) is only 14.3% higher than the number of negative ones (28).

Fig. 3.14  Weekly percentage variations in the number of new cases of Covid-19 in Mexico

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5.2   Weekly Deaths Figure 3.15 shows the weekly trend of deaths due to Covid-19 in Mexico in the 68-week observation period. As expected, this trend is substantially overlapping with that of the incidence. So, again there are essentially two waves: the first one in the spring of 2020 and the second one in late-­ autumn 2020. In this case, however, the isolated peaks are two: the first one contemporary to the intermediate one seen before, the second one, instead, almost at the edge of the 68-week interval. In more details, it can be seen that i. The first wave begins in April 2020 (week 10), two weeks after the first wave of new cases, when the weekly number of deaths increases from 42 to 5313  in mid-June 2020 (week 22). Then it slowly declines, remaining around 4000 deaths for the next ten weeks. ii. The second wave starts in late-November (week 40), four weeks before the second wave of the number of new cases, when the weekly number of deaths increases from 3358 to 9994 in February 2021 (week 55), reaching the highest value of the 68-week interval. Just after four weeks the number of deaths will be more than halved. As mentioned before, there are two isolated spikes: the first, equal to 5018 deaths, in October 2020 (week 37), and the second, equal to 5067 deaths, in April 2021 (week 64), which have similar characteristics to the peak seen in the previous section.

Fig. 3.15  Weekly trend in the number of deaths due to Covid-19 in Mexico

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Fig. 3.16  Weekly percentage variations in the number of deaths due to Covid-19 in Mexico

Figure 3.16 shows the weekly percentage variations of the number of deaths due to Covid-19 in Mexico over time. Also in this case, the most important positive variations are recorded in the weeks of the first wave, but also in the following weeks, there are increases of a certain value, such as those observed in the thirty-seventh week (+90%, compared to the previous week), in the fifty-fifth week (+64%), and finally, in the sixty-fourth week (+104%).

6  Covid-19 in Canada, the EU, and Mexico: Similarities and Differences in the Effects of Infection The numerical dimensions, that is, the different orders of magnitude of the values of the three pieces of information analyzed here, are the result of the speed of spread of the infection, but they also depend on the socio-­ demographic characteristics of the reference Nation; first and foremost, the demographic dimension. This requires some form of standardization of information to be able to compare and fully understand the size and effects of Covid-19 infection in the three areas in question, net of their different demographic dimensions. To support this, it is sufficient to look again (Tables 3.1, 3.2, 3.3) at the total amount of Covid-19 positive subjects detected in 68 weeks in Canada (1,314,420), in the European Union (29,148,227) and, finally, in Mexico (2,371,483). Enormously different values. Such large differences can be

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explained by many things, but first it is necessary to remove the effect of the different orders of magnitude involved. Similar considerations can be extended to the other two pieces of information analyzed here. Therefore, as mentioned above, this section is devoted to compare the three nations with respect to the three information already analyzed in the previous sections. Here, the goal is to bring out differences and/or similarities with respect to when and how the nations were affected by the waves of Covid-19 disease infection and the consequences they caused. The information used here is the same as in previous sections, but now it is used in a standardized form, with respect to the demographic size of each nation, that is in units per million people. As anticipated, this section adds one more piece of information to the usual information, namely, the effective reproduction rate, Rt. Table 3.4 shows some useful statistics to understand how different the three nations are with respect to some fundamental demographic dimensions, also to better understand the evolution of the infection and its repercussions on the populations. Thus, before conducting the comparison, it is necessary to eliminate the effects of all magnitudes that may vitiate the evidence, thus making it uninformative, if not misleading. To this end, therefore, information on new cases, deaths, and admissions to ICUs are related to the population and expressed per million people. Table 3.5 shows some summary statistics of the information under review for each wave and each area. In the following subsections, the information is analyzed in detail. 6.1   Weekly New Cases per Million People Figure 3.17 shows the trends of the weekly number of new cases per million people (i.e., the relative incidence) in Canada, the European Union, and Mexico over the 68-week interval. It can be observed that the Table 3.4  Some demographics of Canada, the European Union, and Mexico

Canada European Union Mexico

Population

Area(Km2)

Density (Population/Km2)

ICU beds (×100,000)

38,033,014.0 447,319,829

9,985,000 4,233,000

3.8 105.7

12.9 537.8

126,014,024.00

1,973,000

63.9

3.3

Canada European Union Mexico Canada EU Mexico Canada EU Mexico

I

III

II

Nation

Waves

330.9 339.6 362 1,464.8 3,006.3 953 1,617.0 2,521.5 –

Peak

New Cases

Apr/20 Mar/20 Jul/20 Jan/21 Nov/20 Jan/21 Apr/21 Mar/21 –

M/Y 13 10 26 50 41 52 64 61 –

Week 35.2 27.8 41 27 57.5 78 9.4 39.7 –

Peak

Deaths

Apr/20 Apr/20 Jun/20 Jan/21 Dec/20 Febr/21 Apr/21 Apr/21 –

M/Y 14 12 22 52 47 55 66 64 –

Week 103.9 163.9 – 162.1 232.2 – 269.7 251.4 –

Peak Apr/20 Apr/20 – Jan/21 Nov/20 – May/21 Apr/21 –

M/Y

ICU Adm.

12 11 – 51 43 – 67 64 –

Week

3.679 2.26 2.269 1.386 1.42 1.359 1.329 1.189 –

Peak

Rt

Mar/20 Mar/20 Mar/20 Oct/20 Oct/20 Jan/21 Apr/21 Mar/21 –

M/Y

8 7 8 41 39 50 63 59 –

Week

Table 3.5  Summary statistics of new cases, deaths, ICU admission, and effective reproduction rate, Rt, by wave, for Canada, the European Union, and Mexico

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Fig. 3.17  Weekly trend in the number of new cases per million people of __ __ Covid-19 in Canada (___), European Union ( o ), and Mexico (...o...)

standardization of the incidence values in the three areas has not substantially modified the trends over the time, even if some differences can be appreciated with respect to what has been seen for the absolute incidence. The most evident one concerns the extent of the variations over the time, which appear “re-scaled” to the respective populations. It should be noted that i. After the first waves, the European Union shows a relative incidence’s curve significantly higher than Canada and Mexico. In fact, as of September 2020 (week 33), the European Union curve is consistently above the incidence curves of the other areas. ii. The three areas show very different peaks in relative incidence, both with respect to the values reached and the time in which they occur. The European Union has the highest peak at 3006.3 new cases per million population in the second wave in November 2020 (week 41); Canada has the highest peak at 1617 new cases per million population in the third wave in April 2021 (week 64); and finally, Mexico has the highest peak at 953 units per million population in the second wave in mid-January 2021 (week 52). iii. The European Union and Canada experience the first wave of infection and thus reach the first peak several weeks before Mexico; in fact, heights and timings of the peaks are: 339.6 new cases per million people at the beginning of April 2020 (week 10) in the European Union; 330.9 cases per million people at the end of April

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2020 (week 13) in Canada; 362 cases per million people, at the end of July 2020 (week 26) in Mexico. iv. The European Union and Canada have weekly relative incidence trends similar in shape, but different both in the heights and in the timings of manifestation; in fact, the European one is always considerably higher and earlier than the Canadian one. Considering (Table  3.4) their population densities (People/Km2), one could think that the considerable difference (105.7/Km2 vs 3.8/Km2, respectively) “in favor” of the European Union could have contributed to produce these differences, that is, the greater the proximity between people, the faster the spread of transmission. v. Mexico shows a different trend in shape and amount. In fact, Mexico experiences only two waves and a relative incidence almost always lower than the other two Nations. Considering its population density (63.9/Km2), Mexico should have a relative incidence curve higher than that of Canada. Finally, it is interesting to note that since February 2021 (week 55), Mexico shows a significant decrease in relative incidence, in contrast to what is observed for the other two nations. In conclusion: –– The EU precedes Canada and Mexico in both timing and relative incidence of the three waves of infection. –– Canada experiences the same number of waves as the European Union, slightly behind in timing, and with a lower relative incidence than the European Union. –– Mexico experiences only two waves, the first several weeks later than its counterparts in the other two nations; it almost always has a lower relative incidence over time than the other two nations; and, finally, disease transmission slows down earlier than in the other two nations. 6.2   Weekly Deaths per Million People Figure 3.18 shows the trends of the weekly deaths due to the Covid-19 per million people (i.e., the relative mortality) in Canada, the European Union, and Mexico over the 68-week interval. Again, mortality standardization has not substantially affected trends over time in the three areas,

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Fig. 3.18  Weekly trend in the number of deaths per million people due to __ __ Covid-19 in Canada (___), European Union ( o ), and Mexico (..o..)

but it has altered the magnitude of changes over time, which appears “scaled down” to their respective populations. All nations show trends in relative mortality like those in relative incidence, with higher values around the peaks of infection. It should be noted that i. The first wave of infection (which has similar relative incidences in the three nations) produces different values of relative mortality in the three nations: highest in Mexico, with 41 deaths per million people (at week 22), then in Canada, with 35.2 deaths per million people (at week 14), and finally, in the European Union, with 27.8 deaths per million people (at week 12). ii. Mexico, at times, shows higher levels of relative mortality than other nations, despite having lower relative incidence than them, and it achieves the highest relative mortality ever observed in the 68-week interval, at 78 deaths per million people (week 55), compared with 57.5 deaths per million people (week 47) achieved by the European Union, and 35.2 per million people (week 14) achieved by Canada. iii. Canada, while having an almost always higher relative incidence than Mexico, has a significantly lower relative mortality than Mexico. Moreover, it is the only nation whose maximum relative mortality coincides with the peak of the first wave, that is 35.2 per million people (week 14), and then is always lower than that of the other two nations.

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In conclusion: –– Mexico, while having lower relative incidence among the three nations, has a much higher relative mortality (especially compared to Canada). –– Canada has lower relative mortality after the first wave. –– The European Union, on the other hand, has a relative mortality that confirms the dramatic impact of high relative incidence. 6.3   Weekly ICU Admissions per Million People As mentioned in the previous sections, at the time of data collection, it was not possible to trace the number of ICU admissions for Mexico. Therefore, Fig. 3.19 shows the trends of the weekly ICU admissions per million people (i.e., the relative hospitalization), limited to Canada and the European Union, over the 68-week interval. Once again, the standardization has not substantially affected trends over time in the two areas, but it has altered the magnitude of changes over time. The greatest pressure on the hospital systems of the two nations is exerted by the last two waves of infection, rather than the first. It should be noted that i. Canada achieves the highest relative hospitalization ever observed, at 269.7 ICU admissions per million people (week 67), despite almost always reporting lower levels of relative hospitalization than the European Union, which instead achieves its highest relative hos-

Fig. 3.19  Weekly trend in the number of new ICU admissions per million peo__ __ ple in Canada (___), European Union ( o )

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pitalization, at 251.4 admissions per million people, in April 2021 (week 64). ii. The European Union suffers a higher relative hospitalization than Canada for a large portion of the 68-week interval. In fact, from July 2020 (week 24) to end-April 2021 (week 65), the European curve is always higher, and often significantly so, than the Canadian one, reaching the maximum distance of about 165 units in mid-­November 2020 (week 42). 6.4   The Rt Index’s Trends in the 68-Week Interval The diffusion dynamics of the different infectious diseases can be explained using mathematical models. The mathematical model that best describes these diffusion dynamics is the basal reproduction rate, also known as R0, or the average number of secondary infections caused by an infected individual within a susceptible population and in the absence of control strategies. The susceptible individual is defined as a member of a population who is at risk of becoming infected by a disease. The index R0 appears to be directly proportional to three distinct factors: the number of contacts per time unit, the probability of transmission per contact, and, finally, the average duration of the infectious period of each case. In principle, an R0 rate less that one is associated with the interruption of the transmission chain of infectious disease and, consequently, the extinction of the related epidemic or pandemic event. Ultimately, we can say that reducing the value of R0 means controlling the spread of an infectious disease. However, the concept of R0 has a significant limitation: it perfectly describes the spread of an infectious disease only within a totally susceptible population. The most realistic situation is when the population is not fully susceptible (at most, it is only susceptible in the first period of an epidemic or pandemic event caused by a new pathogen) because, for example, some contacts can be immune. The effective reproduction rate, also known as Rt, is preferred (Caicedo-­ Ochoa et al., 2020) when it is necessary to describe the spread of an infectious disease within a population that is not fully susceptible to the pathogen. The effective reproduction rate can be calculated by multiplying R0 by the fraction of susceptible individuals within a population. In scientific literature, many methodological approaches exist. We have

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referred to the methodology adopted by Muggeo et al. (2020), based on segmented regression (Muggeo, 2003). The Rt meaning is like that of R0. Suppose Rt is greater than 1, the greater the virus’s contagiousness. For example, an estimated Rt of 1.8 means that 100 infected persons, on average, can infect 180 persons in that period. Usually, the considered period is seven days. This section concerns the weekly estimates of Rt for the three areas considered. As a starting point, the 7-day group starts on January 24, 2020. However, the first records of Covid cases in Mexico date back to February 29, 2020, that is, week 6. Figure 3.20 shows that the first epidemic weeks are the most intense. In fact, the initial phase of the pandemic is the one with the lowest control of Covid-19 disease transmission and, in a few weeks, the infection spreads very fast. In subsequent phases, Rt index values decrease, ranging between 0.6 and 1.4, with values above one predominantly in winter periods. The EU and Canada report first cases around the same time, and the measure of the spread is very high. As mentioned, Covid-19 disease appears later in Mexico, with an even higher measure of spread. The high variability in Rt is probably due both to the high heterogeneity in measuring, collecting, and reporting data, and to the initial smallness of data. In fact, even a few new cases correspond to high percentual variations: 1 person over 10 is 10%. That can suggest the very high peak for Mexico (Rt = 15) and the fluctuating values for the European Union and Canada.

Fig. 3.20  Weekly Rt index’s trends in Canada, the European Union, and Mexico

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Another aspect is regarding the climate characterizing the three areas. Studies have shown that dry and cold circumstances are potentiating factors in spreading the virus (Mecenas et  al., 2020). Data show that, although temperatures were higher in Mexico than in the other regions, there the spread of the virus was higher. That could be due to a health system that is not well developed and adequate for emergencies such as an epidemy. In addition, the country is characterized by a multitude of small rural centers that often lack good health facilities. After the introduction of restrictive measures to counter the spread of the virus, the Rt estimates began to fall and fluctuate around the value of 1. Thus, after the first three months, characterized by a high growth rate of new cases, the absence of accepted and agreed containment measures, and the time needed for the interventions to take effect (typically about ten days), estimates never exceeded the value of 2 until the end of the observation period. Figure 3.21 summarizes Rt estimates via boxplots, by geographic area.

2.00

1.75

1.50

Rt

1.25

1.00

0.75

0.50

0.25 Canada

European Union Area

Fig. 3.21  Boxplot of Rt estimates by area

Mexico

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The greatest variability in terms of the min-max range is found in Mexico, which peaks at 1.78 in September 2020. The distribution of 50% of the observations centered to the median (interquartile range) is quite similar in all three areas. One difference is again noticeable with Mexico, as half of the Rt estimates are below the median and below the value of 1. Fluctuations above/below around the value of 1 are typically attributable to three aspects: . The introduction/removal of containment measures 1 2. The occurrence of a virus variant 3. Vaccine administration Although these aspects are interesting, this chapter aims not to analyze the causes of the spread of the virus or its speed. Therefore, as mentioned above, we have restricted the analysis to describing the pandemic using official data.

7  Conclusions Canada, the European Union, and Mexico: three geographic areas in the northern hemisphere of our planet, different in latitude and longitude, and much more. Different health systems, population size and spread, climate. As we have seen during the development of this chapter, the three areas have been hit in different ways and moments by a variable number of pandemic waves of infection. The trends described here are the result of a cumulative process, where the dimensions reached by the phenomena under consideration in the most recent waves derive from the substantial increases undergone in the first wave. Canada and the European Union faced three waves, characterized by different incidences. The first two waves were substantially contemporaneous in the two areas, but their incidence was dramatically higher in the European Union. On the other hand, Mexico suffered only two waves, the first of which lagged its counterpart in the other two countries, characterized by a relatively lower incidence. The ranking of nations with respect to relative incidence (1st the EU, 2nd Canada, and 3rd Mexico) is very different from the ranking with respect to relative mortality (1st Mexico, 2nd the European Union, and 3rd Canada). Therefore, it might come as a surprise that, still in relative terms, the most dramatic consequences of infection (i.e., deaths) were even more dramatic in Mexico,

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than elsewhere. Even more than in the European Union, where the number of affected individuals over the entire 68-week interval is more than ten times higher than in Mexico. More restrained effects were observed in Canada, whose number of deaths was often lower than in other countries, both in absolute and relative terms. Nothing is known about Mexico’s trend in ICU admissions due to the unavailability of information from the source. Still, given the correlation between admissions and deaths, it can be assumed that, at least in relative terms, it should not differ much from the trend in deaths. In Canada, again in relative terms, the use of intensive care was lower than that observed in the European Union. The effective reproducibility index analysis confirms that the highest infection rate characterized the first wave in all countries. Mexico had higher intensity and heterogeneity index values than the other countries. Except for the first months, during which the initial few cases and the lack of homogeneity of the information collected led to very high and fluctuating estimates, the three areas were characterized by reasonably similar virus prevalence rates. Their fluctuations are recognized as a symptom of the effects of restrictions (imposed or relaxed), the impact of new virus variants, and individuals’ behavior.

References Caicedo-Ochoa, Y., Rebellón-Sánchez, D. E., Peñaloza-Rallón, M., Cortés-Motta, H. F., & Méndez-Fandiño, Y. R. (2020). Effective reproductive number estimation for initial stage of COVID-19 pandemic in Latin American Countries. International Journal of Infectious Diseases, 95, 316–318. https://doi. org/10.1016/j.ijid.2020.04.069 Fletcher, R. H., & Fletcher, S. W. (2005). Clinical epidemiology: The essentials (4th ed.). Lippincott Williams & Wilkins. Mecenas, P., Bastos, R. T. D. R. M., Vallinoto, A. C. R., & Normando, D. (2020). Effects of temperature and humidity on the spread of COVID-19: A systematic review. PLoS One, 15(9), e0238339. https://doi.org/10.1371/journal. pone.0238339 Muggeo, V.  M. R. (2003). Estimating regression models with unknown break-­ points. Statistics in Medicine, 22(19), 3055–3071. https://doi.org/10. 1002/sim.1545 Muggeo, V. M. R., Consiglio, A., Sottile, G., Genova, V. G., Bertolazzi, G., & Porcu, M. (2020). Analysis and monitoring of COVID-19 dissemination in Italy: The CoViSTAT19 group. Statistica & Società, IX(1), 1–4.

CHAPTER 4

We Are All Europeans. EU Institutions Facing the Covid-19 Pandemic and Information Crisis Alessandro Lovari and Marinella Belluati

1   Introduction This chapter investigates how the European institutions’ communication has faced the Covid-19 pandemic, focusing on policies, strategies, and interventions for counteracting disinformation and the spread of problematic messages that could harm citizens and weaken democracy. Indeed, timely and accurate information, alongside the opportunity for citizen participation and feedback, are essential elements of the democratic policy-making process (OECD, 2021). In general, the European Union has gradually evolved from top-down governance to a more inclusive model, involving social and economic

A. Lovari (*) Department of Political and Social Sciences, University of Cagliari, Cagliari, Italy e-mail: [email protected] M. Belluati Department of Cultures, Politics and Society, University of Turin, Turin, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. La Rocca et al. (eds.), Infodemic Disorder, https://doi.org/10.1007/978-3-031-13698-6_4

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partners—and, over time, societal actors—to a greater extent throughout the policy cycle. The adoption of multilevel governance in European policy design is something of an innovation in dealing with the increasing complexity of institutional problem-solving approaches (Piattoni, 2010; Volkmer, 2014). Multilevel governance is used as a policy vision to describe how power is spread vertically between many levels of government, and horizontally across multiple actors where the public and private sectors interact with civil society, where large and small stakeholders share practices, and where the domestic and supranational levels cooperate in formulating normative decisions. Multilevel governance establishes a regulatory system in which organizations are engaged, and where ethics, risk management, compliance and administration become decision frameworks. This is also the decision model adopted to design European disinformation policy in general, which became more effective during the Covid-19 pandemic, the crisis that embodies the contemporary dilemma about increasing trust in the public and political sectors (Belluati & Fubini, 2022). Scholars have drawn attention to contemporary society’s growing sense of distrust in government and in public institutions (Edelman., 2018, 2021), as well as to the pervasive impact of digital technologies on service delivery and on information and communication practices. In what Chadwick (2013) has called an interconnected and hybrid media system, it is interesting to scrutinize the complex and nonlinear interplay between technologies and social actors. Here, processes have been accelerated by the transformation of contemporary media ecologies, marked by the rise of fragmented public spheres (Bentivegna & Boccia Artieri, 2020), and by the increasing use of social media by citizens and public sector organizations. Citizens in particular can play an active role, not only as consumers of information but as prosumers of digital content of general interest— relating for instance to health, the economy, and politics—that can impact democratic processes. This can take place at the individual and collective levels, as witnessed by the activism of social movements and associations on digital avenues, where they also seek to influence public policies and government decisions. Furthermore, these groups’ mass self-­ communication on social media (Castells, 2009) can influence media agendas in those processes of mutual shaping and hybridization that have been named reverse agenda setting (Hermida, 2010) and network agenda setting (Guo, 2014).

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For their part, government organizations and public institutions cannot remain aloof of digital platforms for several reasons. Media consumption patterns have shown that digital avenues play a major role in citizens’ information-seeking practices across the globe (We are social, 2021), while digitization policies have driven the development of e-government and enabled e-participation processes, as well as a gradual migration of public communication toward the Internet and participative platforms (Canel & Luoma-aho, 2019; Lovari & Valentini, 2020). Moreover, an effective, trustworthy, and recognizable voice is needed in digital environments roiled by a cacophony of voices (Dahlgren, 2009), where toxic practices spreading disinformation can harm public debate and drift dangerously into hate speech (Scamuzzi et al., 2021) and incivility (Bentivegna & Boccia Artieri, 2021). All these processes have been challenged, amplified, and put to the test by the Covid-19 pandemic. The crisis demonstrated public institutions’ resilience as they provided timely and reliable information to citizens and the media, especially during the acute phases. In addition, it drew attention to the critical role of public sector communication in fighting an “infodemic,” a mix of facts, fears, rumors, and speculation (Salaverría et al., 2020). The uncertainty surrounding the virus’s etiology and consequences created an omnium-gatherum of messages, where institutional voices overlapped with sensational media coverage and sank into an indistinguishable online mix of misinformation, unverified information, and intentionally manipulated disinformation (Larson, 2020). All these messages and voices spread quickly on digital platforms and traversed the meshes of the contemporary media ecosystem. As a result, government and public institutions were obliged to take a proactive and strategic role in informing citizens, increasing public policies’ accountability, and nurturing trust—an intangible asset heavily challenged by the pandemic crises (Allington & Nayana, 2020; Edelman, 2021; Lovari et al., 2020). All these processes have unfolded at different levels: from the local to the national, up to the international and global. In this chapter, we focus on the supranational level, and in particular on the European level. We highlight the role played by European Union (EU) institutions in dealing with the Covid-19 pandemic and in fighting disinformation by adopting specific policies and communication strategies. After a review of the main concepts and developments in public sector communication, the chapter explores the EU disinformation policy-making process, with its multilevel governance approach to tackling the Covid-19 information crisis.

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Particular attention will be devoted to the EU’s communication initiatives and relationship with digital platforms, key players in this complex scenario. Critical theoretical and practical implications will also be discussed.

2  The Role of Public Sector Communication in Contemporary Informative Environments Public sector communication is always a challenging topic for many reasons. First, the different organization of governments, public administrations, and institutions across the globe makes it difficult to determine the boundaries of where the public sector starts and ends in Western society. Second, the terminology used by international scholars who have investigated communication in the public sector is far from uniform, reflecting the variety of national situations, as well as the perspectives taken by different disciplines and theoretical frameworks (e.g., Bessières, 2018; Canel & Luoma-aho, 2019; Ducci et al., 2021; Graber, 1992, 2003). In Italy and France, for instance, scholars have frequently used the term “institutional communication” to refer to communicative strategies and practices related to public services, transparency, and public engagement, as opposed to partisan communication activities. The most commonly used expression appears to be public communication, which has recently been adopted by international organizations such as the Organization for Economic Co-operation and Development (OECD), though this usage is not embraced by public relations scholars, who prefer to apply the term to communication flow addressed to different publics, regardless of the type of organizations involved. The need to define this function has prompted scholars to broaden their sights in seeking a common vocabulary and area of inquiry. A major effort in this direction was made by Canel and Luoma-aho, whose intensive research culminated in two books published in 2019 and 2020 that identified trajectories of public sector innovation relating to the domestication of digital technologies, stressing the role of intangible assets such as trust, reputation, engagement, and transparency. They used the expression public sector communication, a term also adopted by Graber (1992) in one of the field’s seminal publications. Canel and Luoma-aho (2019, p.  33) define public sector communication as a “goal-oriented communication inside organizations and between organizations and their stakeholders that enables public sector functions within their specific cultural and/or

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political settings, with the purpose of building and maintaining the public good and trust between citizens and authorities.” This is a broad definition that points out not only the institutional aims and types of messages but also the multiple relations with the different parts that constitute organizations in the public sector (administrative/political/bureaucratic), as well as the relationships with external stakeholders like citizens and the media. Public sector communication is seen as an organizational function to deliver information, listen, and respond to citizens in the service of the common good (OECD, 2021; Graber, 1992). In recent decades, however, scholars have increasingly recognized communication’s role as a policy-­making instrument that can also enhance participation and citizen engagement (Canel & Luoma-aho, 2019; Lovari et al., 2020; Luoma-aho & Canel, 2020; Macnamara, 2017). From this perspective, public sector communication interplays and hybridizes with what the literature calls government communication (Canel & Sanders, 2014; Sanders & Canel, 2013), a term used to describe the non-partisan communication of the executive arm of governments, rather than communication promoting a political party or politicians. Thus, it is distinct from political communication, which is linked to partisan debate, elections, or promoting individual political figures and parties (Ducci et al., 2021; OECD, 2021). Moreover, public sector communication should not only deliver information to citizens and media outlets, in a one-way broadcasting model. Rather, it should instead be seen as a way of enabling institutions to engage in two-way conversations and create opportunities for dialog, collaboration, and participation. This process has been facilitated by digital technologies and social media that provide public organizations with the opportunity to engage a broader variety of stakeholders (i.e., citizens, associations, journalists, companies, labor unions), including those from traditionally underrepresented segments of the population. In turn, they can help truthful and transparent public content reach a wider audience and strengthen trust in government and public institutions as sources of information (OECD, 2021). In this connection, public sector communication can provide strategic leverage for pursuing open government principles of transparency, collaboration, and participation (Lathrop & Ruma, 2010), and can serve an ethical function in combating disinformation with transparent, truthful, and accurate information, raising citizens’ awareness and their engagement (Matasick et al., 2020).

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The Covid-19 pandemic made public sector communication more vital than ever as a means of (re)building relationships based on trust between institutions and citizens (OECD, 2020), in hybrid and convergent media ecosystems with a glut of conflicting messages and problematic information not only about the virus, but also about vaccination and governments’ actions at the national and supranational level. In a recent publication, the OECD (2021) described the new backdrop for public sector communication, highlighting the complexity of this function. Governments and institutions act in an information ecosystem where a plurality of actors contribute to producing and sharing messages at the local and global levels: media, digital platforms (Meta, Twitter, Microsoft, Google, etc.), citizens, companies, and civil society. This contemporary information system also entails specific threats and opportunities that shape the public debate and the flow of public sector communication, as well as of information in the public interest. For instance, the rapid digitization spurred by Covid-19 lockdowns obliged public sector organizations to invest in digital communication and to colonize social media and other online platforms (i.e., instant messaging apps) to reach citizens and the media quickly. Via these digital avenues, citizens can express their voices and expectations, influencing policy-making and political decisions at the individual and aggregate level (i.e., the “Fridays for Future” movement for climate change). Furthermore, this ecosystem is a hotbed of misinformation and disinformation (Giglietto et  al., 2019) that impacts on citizens’ trust (Eurobarometer 2018, 2021), undermining the authenticity of public debate around activities and policies adopted by institutions, including national governments and supranational institutions (Brennen et al., 2020). Often, disinformation is shot through with hate speech and incivility, leading to polarized opinions and online “shitstorms” (Han, 2017) that can tarnish leaders’ reputations and erode institutions’ legitimacy. In the OECD framework, effective communication in the public sector rests on two pillars: (a) institutional and governance prerequisites, which include effective strategic management of communication offices and public relations activities, supported by human and economic resources; (b) strategic communication, which includes careful planning of the activities to be carried out, supported by data, reports, and insights that can be useful in creating public communication flows and monitoring their impact. These two pillars can contribute to achieving intermediate and long-term outcomes such as greater transparency, accountability, and

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stakeholder participation, more resilience to disinformation, and regained trust in public institutions. The framework identifies the key policy catalysts for effective public sector communication. Like any other “one size fits all” model, the framework does not fully consider the structural, organizational, and legal differences between different types of public organizations, and underestimates the complex institutional and cultural settings in which technologies are embedded (Contini & Lanzara, 2009; Lovari & Valentini, 2020). At the same time, it is interesting to see how this framework can be applied and problematized in the specific case of the European Union institutions, focusing on the strategic communication they deployed to fight disinformation and face the Covid-19 information crisis in 2020. 2.1   European Communication Management. The European Multilevel Model From these general remarks, we will now turn to the European level, midway between the wider international dimension of the West and the creation of a supranational European public space. The Covid-19 crisis has revealed that public decisions are increasingly the result of strategies involving supranational actors, and before going into the specificities of the pandemic crisis, it should be pointed out that European regulatory and governance models have always been based on a multi-level and multi-­ dimensional perspective. In this governance approach, local and regional institutions have gradually taken the lead in the European Union’s regulatory system, where regional institutions are particularly influential in the integration process. There are three key features of this model of governance (Marks et al., 1996): 1. Decision-making competences are shared by actors on different levels, rather than being vested in a single centralized actor: the influence of supranational institutions such as the European Commission, the European Court of Justice, and the European Parliament does not exceed that of other actors involved in policymaking processes. 2. Collective decision-making among states leads to a significant loss of control for each Member State. 3. Political arenas are interconnected: subnational actors operate in national and supranational arenas, creating transnational associations in the process.

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However, governments and public opinion do not always understand or accept the impact of this complex of decision-making. In the case of the European institutions, decision-making clearly suffers from a democratic deficit (Pasquino, 2002; Norris, 2011) fueled by the overly technocratic nature of the EU, which draws attention to the problems posed by the EU institutions’ increased competences and the persistent resistance of the political sphere and information systems to coming to grips with this complexity and clarifying their public functions. This creates a permanent gap between the European institutions and the Member States that stands in the way of effective European citizenship. National political and institutional systems still struggle to include the European level on their horizon, even when domestic consensus is not an obstacle. For their part, media systems still show a lack of awareness and face objective difficulties in covering European news and presenting European issues (Belluati & Marini, 2019; Righetti et al., 2019). This has negative repercussions, as the public often receives superficial or erroneous news about the impact of European decisions on the domestic public sector’s policy-making. Not only does the European Union have an undeniable democratic deficit, but it has also been argued that European public sector communication is in such a fragile condition as to legitimize the notion of an “information deficit” (Trenz, 2008; De Vreese, 2007), referring to the European institutions’ chronic difficulty in communicating with citizens and providing clear and simple information about themselves and their work. This is also why EU communication has become essential for implementing the integration process and reducing the democratic deficit. EU public communication can be defined as “the activity promoted by public sectors at European, national and regional level to inform and promote democratic debate, developing a sense of European identity, based on common values, history and culture” (D’Ambrosi, 2019, p. 41). The Charter of Fundamental Rights of the European Union recognizes the primacy of public communication as the legal basis of the EU’s relationship with citizens. Fully aware of this, the European institutions have, over time, strengthened their communication strategy, establishing specific organizational structures and policies. To fully understand how EU public communication unfolds, we must focus on the three different levels on which it operates: (a) communication from the European Union, that is, the central communication activities carried out by the European institutions; (b) communication for the European Union, carried out by the European communication offices in

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the Member States (EU Representations, Europe Direct, EU, EU diplomacy); (c) communication about the European Union, that is, all relationships between the European institutions and the information system and political journalism (Belluati, 2020) at all levels (international, national, and local). The main aim of the European public communication policy is to increase knowledge of activities carried out in the interest of the Community to “cultivate” European citizenship and increase trust in the integration process. While citizens are the main target group, the public and private sectors at all levels, and civil society as well as the media and the information system are also important interlocutors. Since its foundation in 1958, the European Union—then called the European Economic Community—has adopted a communication strategy. In 1973, the European Commission opened the Directorate General for Communication, DG X.  Communication was initially a diplomatic activity aimed at governments, but attention has increasingly turned to information systems and the public communication sector (Santaniello, 2013). Since the 2000s, however, the European Union, and the European Commission in particular, have been working to reorganize the public communication sector, adopting structures and regulations to facilitate the circulation of internal and external information and improve communication with European citizens. Major efforts have been made to improve the coverage of the EU’s activities by improving transparency and accessibility and simplifying its functions at all three levels of communication. In full compliance with EU policy guidelines, European communication flows have adopted a multi-level governance model, where coordinated action by the Union, the Member States and regional and local authorities is based on partnership and aims at defining and implementing EU policies.1 Every European institution now has a Directorate General (DG) and specific communication sectors that work closely with the institutions and complement each other. The European information world operates at various levels (local, national, and international) and fields strategies for managing different communication tools and environments, which are well supported financially. In 2006, the White Paper on Communication2 1  https://cor.europa.eu/en/about/secretary-general/Pages/CoR-communications. aspx. Accessed February 2022. 2  https://europa.eu/documents/comm/white_papers/pdf/com2006_35_en.pdf. Accessed February 2022.

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stated the need to expand the EU’s partnership approach to include all key actors: not only public institutions and the mainstream media and information system, but also political systems, the private sector, civil s­ociety, and all formal and informal stakeholders in public communication. Initially designed with the legacy media in mind, European communication policy soon shifted its main focus to the online environment (websites, social media, etc.). This strategy established a new actor network in the public space that would become crucial in managing information disorder. The European information ecosystem (Fig.  4.1) updates Habermas’s definition of the European public sphere (Habermas, 2015) as a complex and interdependent multi-level and multi-actor system. The center of the ecosystem is the strategy formulated by the European Commission, the EU’s executive arm and most powerful institution. The ecosystem also includes other European institutions’ initiatives and encompasses a galaxy of organizations, functions, professions, and relationships that reflect its multidimensionality. Related to it and crucial to the success of the communication policy are the other communication levels making up the European ecosystem. There is the level of institutional relations with the communication structures of the Member States. Then there is the complex relationship with European political parties and with national parties

Fig. 4.1  European Communication Ecosystem. Source: Authors’ property

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in the European Parliament’s political groups. No less important, however, is the ongoing relationship with active and organized civil society, national media systems, and the still little-developed European media system. Lastly, the ecosystem considered in the communication strategy includes the complex, and often problematic relationship with digital platforms, now crucial players in communication flows. Managing European public sector communication thus seeks to activate a strategic governance model aimed at creating and distributing communication flows at all territorial (European, national, and local) and functional levels (public administration and information offices, civil society, mass media, economic and social partners) following the process of vertical and horizontal subsidiarity (Bee & Bozzini, 2016). Despite this structural investment, it is not so simple for European public communication to coordinate all these plans and layers. There is a problem of harmonization of internal and external communication within and between institutional levels that have different institutional aims. In addition, national journalism, and the national media systems in general, continue to devote little space to European news content and show a lack of attention to European agenda-setting. Though European institutions provide training resources for national and local information officers and try to support European journalism projects (Belluati & Marini, 2019), the European public agenda is still far from asserting itself. In addition, though the relationship with civil society has been strengthened by the work of the national EU Representations and the Europe Direct activities (EDs) on the ground, it has not yet managed to make a systemic impact. Lastly, the relationship with the European political level, which is still deeply concerned with national sovereignty, is still very much a work in progress. For all these reasons, and despite the work that has been done, the European communication deficit persists. News from Europe continues to be too cold, fragmented, and difficult to spread, producing boomerang effects for the Community institutions themselves. Accordingly, the fight against disinformation suggests itself as a policy case study that can help us understand progress and resistance in the management of good global communication policies. In the specific case of the Covid-19 pandemic, a number of potential weaknesses proved to be strengths, as European institutions were able to rely on a multidimensional public communication approach that had been launched well before the perverse effects of the pervasive role of digital platforms and the

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infodemic became apparent, dictating a thorough rethinking of public sector communication strategies.

3  European Strategies: Tackling Disinformation and Covid-19 Crisis 3.1   Reacting to Covid-19 Against Domestic Paralysis The first officially recorded cases of SARS-CoV-2 in the European Union date to January 24, 2020. Even before, on January 17, 2020, the ECDC (European Centre for Disease Prevention and Control) held its first meeting to discuss the main risks of the burgeoning number of cases in China and neighboring Asian countries. Following the first cases in Europe, the European Civil Protection Mechanism was immediately activated to repatriate the Europeans in Wuhan (China), and 10 million euros were allocated for research. On February 13, 2020, the European Council held its first extraordinary meeting on the novel coronavirus emergency, in which the EU Health Ministers approved the first emergency measures to be managed by the European Commission. On February 24, the Commission announced an economic aid package of 232 million euros, appealing to the principles of internal solidarity in order to counter the first waves of misinformation about the distribution of aid funds and the internal tensions between the so-called “frugal states”3 and the hardest-hit countries. On March 2, 2020, a European emergency team was set up to coordinate the EU’s actions and to support the individual states’ objective difficulty in facing the epidemic crisis. At the same time, a website (“Coronavirus response”) with data on the measures that had been introduced was launched in several languages for the general public and target groups.4 On March 4, 2020, the Eurogroup5 produced an economic and financial damage assessment of Covid-19’s impact and, together with European health ministers, stressed the need for general supranational coordination 3  The “frugal states” were Austria, Denmark, Finland, the Netherlands, Sweden, and at first, Germany. See https://ecfr.eu/publication/the-transformative-five-a-new-role-for-the-­ frugal-states-after-the-eu-recovery-deal/. Accessed February 2022. 4  https://ec.europa.eu/info/live-work-travel-eu/coronavirus-response_en. Accessed February 2022. 5  The Eurogroup is the European coordination center that brings together the finance ministers of the Member States that are part of the Eurozone and adopt the euro.

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to manage the crisis. Also in March, in a joint videoconference, the European Council, Commission President Ursula von der Leyen, European Central Bank (ECB) President Christine Lagarde and Eurogroup President Mario Centeno announced their main common objectives: to limit the spread of the virus, secure medical equipment, promote vaccine research, manage the socio-economic crisis, and improve the flow of information within the Union. This was followed by a series of official video messages by the leaders of the European institutions on national news and official social media channels. Between March and July 2020, the European Commission worked to build greater coordination between the Member States, launching a huge economic and financial plan.6 Given the urgency of the situation, the proposals were accepted by the European Council in a very short time and without modifications. These decisions added to the three safety nets introduced by the EU to support workers, businesses, and countries7 and, in a historic agreement, EU leaders established a 750 billion euro “Recovery Fund” which European Council President Charles Michel hailed as “a concrete signal that the EU is capable of taking strong action.”8 Although health is not an area of direct intervention, Europe allocated 3 billion euros for supplies and hospitals and 1.4 billion euros for medical research, linking this commitment to the project for a European platform

6  Some of the main measures included increasing the flexibility of the European budget, providing more liquidity for European banks, and postponing financial deadlines. An additional € 1 billion was released from the European Fund for Strategic Investments (EFSI) for small and medium-sized enterprises. A € 824 billion financial plan was approved for the period 2021–2027. The Next Generation EU (NGEU) program was launched to support investments in green and digital transitions, and the Re-open EU website was set up to encourage the tourism sector https://reopen.europa.eu/en/. The ECB (the Central Bank) launched a massive government bond purchase program for € 1350 billion, and the EIB (the European Investment Bank) mobilized € 40 billion for business support. In addition, € 37 billion in structural funds were released, and new conditions and rules were laid down for using the Fund for European Aid to the Most Deprived (FEAD) https://ec.europa.eu/ social/main.jsp?catId=1089&langId=en. Accessed February 2022. 7  The SURE European unemployment fund supporting small and medium-sized enterprises and the many workers in difficulty should also be mentioned. 8  https://www.consilium.europa.eu/en/policies/eu-recovery-plan/. Accessed February 2022.

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for collecting and sharing data on Covid-19.9 In addition, it announced a World Health Summit in 2021, the year of Italy’s G20 Presidency. Europe also pumped significant funds into vaccine research and purchases through Advance Purchase Agreements10 with individual vaccine producers. The European Commission became a major player, obtaining the right to buy a certain number of vaccine doses over a certain period of time and at a certain price. In return, the Commission financed part of the initial costs from the 2.7-billion-euro emergency support facility. This funding was considered as a down payment on the vaccines that Member States would buy.11 The European plans have been enormously wide-ranging and missteps have admittedly been made, but by deploying their institutional competences, the European institutions maintained a clear capacity for action at a time when the individual Member State was paralyzed by the situation, thus gaining credibility in the public eye. A recent Special Eurobarometer survey12 of more than 26,000 citizens over 15  years of age, conducted by the European Parliament between March and April 2021  in the 27 EU countries, found that 48% of Europeans were satisfied with the measures taken by the EU to respond to the pandemic (5% were very satisfied). At the same time, 74% totally agree or tend to agree that the EU should have more competences to deal with crises. Europeans think that to respond to the crisis, the EU must prioritize action on vaccines; the second priority is investing in medical research, followed by formulating a strategy for future crises.

9  The European Commission has launched the new European health program, EU4 Health, to strengthen the EU’s response capacity. https://ec.europa.eu/health/funding/ eu4health-2021-2027-vision-healthier-european-union_en. Accessed February 2022. 10  Advance Purchase Agreements (APAs) are so-called “pull” incentives meant to encourage and de-risk companies’ investments to develop and produce products for which society has a need. APAs are mostly applied in areas where the market does not provide enough “pull” incentives to enlist a company to make the necessary investments. https://medicineslawandpolicy.org/2021/07/new-analysis-advanced-purchase-agreements-for-covid-­19-­ vaccines/. Accessed February 2022. 11  https://ec.europa.eu/info/live-work-travel-eu/coronavirus-response/public-health/ eu-vaccines-strategy_en. Accessed February 2022. 12  European Parliament Eurobarometer: Resilience and Recovery, Public Opinion One Year into the Pandemic, Spring 2021 https://www.europarl.europa.eu/at-your-service/it/ be-heard/eurobarometer/spring-2021-survey. Accessed February 2022.

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The state of emergency thus enabled the European institutions to speed up the complicated decision-making method of the European Council,13 consisting of representatives of the Member States who have the final vote on European choices. European Commission President Ursula von der Leyen and the Parliament President David Sassoli came to the fore as ­public leaders, gaining unprecedented media visibility. On September 16, 2020, in her first speech to the European Parliament on the State of the Union, von der Leyen proudly emphasized that Europe’s action in response to the outbreak of the Covid-19 crisis demonstrated the benefits of overcoming national sovereignties for the European common good,14 underscoring how important it is that “we are all Europeans.” 3.2   The European Fight Against Covid Disinformation European action was not limited to economic and financial measures. There was also a massive focus on disinformation and information distortion, urgent issues which became very evident during the pandemic. The European institutions immediately activated their own communication structure and a multi-channel strategy to launch messages of reassurance and support to counteract the more negative communication (Ferrera et al., 2021), and President von der Leyen did herself credit as a public leader in the media debate (Drylie-Carey et al., 2020). Since March 2020, European media attention has reflected the global dimension of the Covid-19 health crisis. During this time and in general, the impact of misinformation on the media ecosystem has become clearer in many ways. The crisis has highlighted the effects of communication systems’ hybridization as a result of digitization and has greatly increased the need for reliable information on Covid-19. It uncovered newly critical aspects of journalistic work and called the media industry’s sustainability into question. Lastly, it revealed the cognitive distortions produced by the

13  https://www.consilium.europa.eu/en/council-eu/decision-making/. Accessed February 2022. 14  Public Speech on 16 September 2020 https://ec.europa.eu/commission/presscorner/detail/en/SPEECH_20_1655. https://www.linkiesta.it/2020/09/discorsocompleto-­stato-dellunione-ursula-von-der-leyen-europea-commissione-futuro/. Accessed February 2022.

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spread of disinformation, particularly on health issues.15 The fight against misinformation is proposing a new vision in dealing with the social impact of communication where formal and informal environments and public and private actors are hybridized, encouraging us to consider communication as an ecological space (Colombo, 2022) where roles are blurred, and competences must be multiplied. During the Covid-19 crisis, the unprecedented spread of fake news destabilized a public discourse marked by uncertainty and fear. During the acute phases, information disorder (Wardle & Derakhshan, 2017), or “infodemic” clearly called for massive interventions. The European Union and its institutions took prompt action to counter misinformation and the circulation of fake news, especially in online media (D’Ambrosi et  al., 2021). Inspired by the lessons learned in the United States, where the pernicious power of misinformation was first revealed, the European strategy began in 2016 in the midst of Brexit’s negative effects and in view of the 2019 European elections (Tumber & Waisbord, 2021). Fighting misinformation was an imperative for the EU’s public action and public space, as was confirmed by a 2018 Eurobarometer survey,16 where 83% of the 26,000 respondents stated that fake news is a “danger to democracy.” Two-thirds of the sample trusted traditional media (70% radio, 66% television, and 63% print), while online information was considered much less credible. All this evidence prompted European institutions to move ahead with the complex strategic policy plan launched in 2016 by the European Commission. In January 2018, the High Level Expert Group (HLEG) on Fake News and Online Disinformation was set up to advise on policy initiatives. Its recommendations called for more transparency about sponsored content and news production, providing an enabling environment for media pluralism, ensuring media system accountability, and the full involvement of civil society. After discussions with strategic stakeholders and an intensive public consultation process lasting two years, the HLEG drafted the “Action Plan against Disinformation,”17 which identified four 15  See CoViD-19 and the Media: Devastation or Renaissance? Euromedia Research Group Policy Brief, http://euromediagroup.org/mdm/policybrief01.pdf. Accessed September 2020. 16  Fake news and disinformation online, Flash Eurobarometer 464, April 2018 https:// europa.eu/eurobarometer/surveys/detail/2183. Accessed February 2022. 17  https://ec.europa.eu/info/publications/action-plan-disinformation-commissioncontribution-­­european-council-13-14-december-2018_en. Accessed February 2022.

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priority intervention areas: (a) improving technological tools for analyzing online disinformation; (b) improving cooperation in EU debunking activities to provide joint responses to threats; (c) improving cooperation with online platforms; (d) raising awareness and improving educational skills in recognizing and combating disinformation. The action plan has five objectives: disrupting the advertising revenues of accounts and websites that spread misinformation; improving the transparency of web advertising policies; addressing the issue of fake profiles and online chatbots; ­empowering consumers to report untrustworthy content by accessing different web sources while improving the visibility and availability of verified content; and empowering the research community to monitor online misinformation by accessing data from platforms while respecting privacy. This plan was followed by the Code of Practice on Disinformation, which was voluntarily, albeit reluctantly, signed by several platforms, major social networks, advertisers, and the advertising industry. As we will see in the following section, this can be considered a strategic success for the European Union’s relationship with the digital platforms. By adopting a multilevel approach, the European institutions are attempting to establish a policy hub as a regulatory umbrella for the individual Member States. However, having a common regulatory framework has advantages and disadvantages. The advantage is that the negotiating power of the European institutions can be greater and more effective than that of the Member States taken singly, as shown by the agreement reached with the main digital platforms and by the establishment of fact-checking networks in the EU. The disadvantage lies in the fact that the final decisions are not binding: given the complicated method of intergovernmental co-decision, the European institutions can only intervene in some fields with deontological instruments that have no legal force. Moreover, over-­ regulation risks missing the cultural specificity of disinformation, which is strongly determined by linguistic practices and by the relationship with the context in which it arises. An additional resource that European policymakers have begun to use to counter misinformation on Covid-19 is the European Digital Media Observatory, or EDMO.18 Launched in 2020 though planned earlier, EDMO supports debunking policies through public and private research networks that identify technological solutions and build granular fact-­ checking services. EDMO seeks to create a community of actors, media  https://edmo.eu/. Accessed February 2022.

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literacy practitioners, and fact-checkers, doing so in several phases. The first phase focused on deploying the core service infrastructure. The second phase, which started in 2021, launched eight national hubs to intercept and counter disinformation campaigns originating in different quarters. In this second phase, a community of debunkers was set up, which currently consists of 94 members spread across all EU countries (Belluati & Fubini, 2022). The third phase was implemented in 2022, and aims to gather a network of fact-checkers specializing in specific issues to be even more precise in combating disinformation and misinformation. Lastly, Europe made massive investments in applied scientific research from 2018 to 2021, especially in the technological resources and artificial intelligence tools for debunking and prebunking, through Horizon 2020 projects and European Research Council grants (ERC).19 Prebunking is a noteworthy innovation in the European strategy against disinformation. It can be a resource for journalists, fact-checkers, governments, and citizens, training them to recognize and deconstruct misleading messages.20 As has been borne out by recent research in experimental cognitive psychology (Maertens et  al., 2021), prebunking can anticipate people’s sentiments and build defensive “barriers” as part of public counter-narrative. The practice raises ethical questions about targeting processes and the power of digital tools to influence, another fundamental issue now being scrutinized by European policy-makers. The point is to deploy disinformation recognition mechanisms that are ethically correct and can rebuild trust between the public and information sources. The tsunami of false and misleading information and attempts by foreign actors to influence internal debates in the EU during the pandemic (Lovari, 2020) thus found the European institutions prepared in terms of strategy and resources. Misleading health information, dangerous hoaxes, conspiracy theories, and attempts to scam and defraud consumers could threaten public health as much as the virus itself. The EU institutions have been working to raise awareness of the dangers of Covid-19 disinformation by promoting the use of authoritative sources and encouraging online platforms to help combat it. This effort resulted in the suspension of over 19  Funded projects in the fight against disinformation https://ec.europa.eu/info/live-­ work-­t ravel-eu/coronavirus-response/fighting-disinformation/funded-projects-fight-­ against-disinformation_en. Accessed February 2022. 20  https://firstdraftnews.org/articles/a-guide-to-prebunking-a-promising-wayto-inoculate-agains. Accessed February 2022.

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3.4 million suspicious Twitter accounts related to the Covid-19 debate since the beginning of the pandemic. On June 10, 2020, the European Commission and the High Representative of the Union for Foreign Affairs and Security Policy issued a joint communication to the European Council entitled “Coronavirus: EU strengthens action to tackle disinformation,” which presented the main lines of action,21 including increased support for fact-checking, strengthening the EU’s strategic communication capacity and building better cooperation with international partners and platforms. From the outbreak of the pandemic until the present, the Commission has continued its debunking efforts via a dedicated webpage22 (“Fighting disinformation”), and information has also been disseminated on official EU social media channels. The EUvsDisinfo website,23 for example, exposed more than 550 disinformation narratives from Russian sources in 2020 alone. European efforts pursued two main thrusts, first, dealing with online news about the pandemic and the spread of the virus, and later with vaccines, where disinformation campaigns are still under way, often based on conspiracy theories. Given the rise of such theories about Covid-19, especially online, the European Commission and UNESCO24 are working on tools that could also be used as a reliable source of information to help institutions and citizens identify, debunk, and counter conspiracy tendencies. Paradoxically, the Covid-19 crisis has become a test case for the ability of the EU and democratic societies to assert their role in handling global problems where individual actions are unlikely to be able to counter deleterious effects, as is demonstrated by the EU’s integrated strategy to combat disinformation through attention to digital environments and the growing role of platforms.  Accessed February 2022.  https://ec.europa.eu/info/live-work-travel-eu/coronavirus-response/fighting-­ disinformation_en. Accessed February 2022. 23  This is the flagship project of the European External Action Service’s East StratCom Task Force set up in 2015 to forecast, address, and respond to the Russian Federation’s ongoing disinformation campaigns affecting the European Union and its Member States. See https://euvsdisinfo.eu/. Accessed February 2022. 24  https://ec.europa.eu/info/live-work-travel-eu/coronavirus-response/fighting-­ disinformation/identifying-conspiracy-theories_en; https://en.unesco.org/themes/gced/ thinkbeforesharing. Accessed February 2022. 21

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3.3   The Problematic Relationship with Platforms During Covid-19 Crisis As mentioned above, the multi-level, multi-actor strategies implemented by the European institutions have also involved specific actions and interventions to establish relations with digital platforms and online companies. Today, these groups have a crucial role in the information market, not only in disseminating information, but also in reducing the circulation of disinformation and misinformation that could harm the European public sphere and the quality of democracy (Belluati, 2020; D’Ambrosi et al., 2021). Digital platforms have transformed the news business model by shifting advertising budgets to leading technology companies, with a rapid decline in traditional media, sending the printed news industry into a crisis (Martens et al., 2018). At the same time, low-quality websites have proliferated, often associated with sensationalized content and clickbait headlines. This trend can have consequences on the quality of the information ecosystem and its role in sustaining democracy (Giglietto et  al., 2019; Matasick et al., 2020). Social media and digital platforms are not just channels for transmitting and sharing messages. Scholars have started to use the concept of “platformization” to describe the rise of platforms and its impact on societies and organizations (Boccia Artieri & Marinelli, 2018; Helmond, 2015; van Dijck et al., 2018). Platformization affects all sectors of society, involving institutions at every level (local, regional, national, supranational). Van Dijck (2020) emphasized that this process may be a struggle for government and public sector organizations, since the risk is that of treating common goods (such as health or education) as privatized commodities encapsulated in a platform ecosystem based on commercial values and specific business models. Public sector organizations seem to be increasingly dependent on platforms, and their communication is constantly shaped and embedded in social media logic and is influenced by the opacity of the algorithms behind the platforms. The platformization of public sector communication (Ducci & Lovari, 2021) has an impact on transparency, citizen engagement, and privacy as well as on the spreading of disinformation and hate speech. Consequently, it can undermine public discourse and the democratic process, thus requiring public communicators to develop new skills and a more critical approach.

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European institutions started to seriously consider these problematic relationships with digital platforms with the approval of the Code of Practice on Disinformation in October 2018, signed voluntarily by the online platforms Facebook, Google, Twitter, and Mozilla, as well as by the trade association representing online platforms (EDiMA), the trade associations representing the advertising industry and advertisers (the European Association of Communications Agencies [EACA], IAB Europe, and the World Federation of Advertisers [WFA]). Microsoft joined the Code in 2019 and Tik Tok in 2020, as well as the Czech, Danish, French, and Polish national associations affiliated with EACA. Monthly reports were posted on the EU Commission website, together with an annual self-assessment report published in October 2019, detailing the signatories’ efforts to fulfill their commitments with the European Commission. In 2020, due to the spread of the Covid-19 pandemic, the online platforms’ implementation of their commitments under the Code of Practice on Disinformation were strategically taken up in Joint Communication 8/2020, “Tackling Covid-19 disinformation—Getting the facts right.” In the document, the Commission called on online platforms to ensure greater transparency about Covid-19 disinformation, promote authoritative information and data from the WHO, national health authorities, and professional media outlets, remove content that could harm or affect public safety, including social media advertising, and report manipulation and malign influence operations as well as coordinated inauthentic behaviors.25 The document also specified the need to reinforce the monitoring and reporting program under the Code of Practice, focusing on Covid-19-related disinformation and misinformation, also involving platforms like WhatsApp and TikTok that were not signatories to the first version of the Code. In addition, the Commission asked platforms to provide data on flows of advertising containing implicit or explicit reference to Covid-19  in order to have a better picture of the actors involved in these campaigns, as well as to connect them with the reports of other EU projects for combating disinformation, like the European External Action Service (EEAS)26 Strategic Communication division and its task force. This was an important step in pursuing the multilevel strategy, and also 25  https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020JC0008. Accessed February 2022. 26  https://eeas.europa.eu/headquarters/headquarters-homepage_en. Accessed Februar y 2022.

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had strategic and organizational impacts for possible interconnected interventions, both in communications and policies. The monitoring program consisted of two stages: (a) a first stage for reporting on procedures and policies put in place up to July 31, 2020; (b) a second stage from August to December 2020, consisting in monthly reports where platforms were required to demonstrate the effectiveness of their policies in curbing Covid-19-related contents. An assessment of the Code of Practice on Disinformation27 (SWD 180/2020) was published in September 2020. The assessment concluded that the Code was a very valuable tool for tackling misinformation, as it provided a framework for a structured dialog between European institutions and relevant stakeholders to ensure greater transparency and accountability of platforms’ policies against disinformation on various topics (i.e., politics, Covid-19). The Commission Staff Working Document also noted that in order to ensure consistent application across stakeholders and Member States, the Code of Practice should be further improved in several areas by providing commonly shared definitions, clearer procedures, transparent key performance indicators and appropriate monitoring. From June 2020 to January 2021, five sets of reports containing six specific documents, produced by the main digital platforms and online service providers (Facebook, Microsoft, Twitter, TikTok, Mozilla, Google) were published in the Study and Report section of the European Commission’s “Tackling online disinformation” webpage. Microsoft’s reports include a specific focus on LinkedIn and Bing, while the Facebook reports also include Instagram. The 30 accessible reports vary in length (from a minimum of 7 to a maximum of 21 pages), content structure, and organization, due to the different affordances and digital services offered by the platforms. Nevertheless, the documents share certain features, as they all cover: (a) Measures taken to reduce false and misleading information, in particular by removing messages liable to cause physical harm or impair public health policies. (b) Action taken to increase the visibility of authoritative sources by giving prominence to Covid-19 information from the WHO and national health organizations. 27  https://ec.europa.eu/newsroom/dae/document.cfm?doc_id=69212. Accessed February 2022.

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(c) Availability of free Covid-related advertising space to government and healthcare organizations. (d) Collaborations with researchers and fact-checkers, thus increasing the visibility of fact-checked content. The December 2020 report indicated that disinformation has also started to appear about Covid-19 vaccines, seeking to undermine the first European vaccination campaign planned for the end of that month. In general, the reports tended to emphasize the platforms’ commitment to increasing the visibility of official sources or their efforts to create specific initiatives such as Twitter’s #ThereIsHelp and Twitter Events Pages, the Facebook Covid-19 Information Center, the #StayHome and #WithMe campaigns launched by YouTube, or the Project Halo campaign by TikTok, which involved physicians and researchers from the EU.  Attention was also devoted to analyzing video, tags and hashtags, both to detect and prevent misinformation as well as to collect data related to the impact of fact-checking, policy violations, click-through rates, and the numbers of vicious ads removed or blocked. For example, the documents reported that Facebook in November 2020 removed over 360,000 pieces of content on Facebook and Instagram containing false preventive measures and exaggerated cures; YouTube removed 30,000 videos that included claims about Covid-19 vaccination that contradict consensus among health authorities; Twitter, in one month, removed 1169 promoted tweets that violated Covid-19 policy and suspended 666 accounts; LinkedIn redirected any member who entered a search for the words “coronavirus” or “#covid” to the link labeled “Know the facts about coronavirus,” which sends members to its official page on the coronavirus. In view of the success of this collaboration, the European Commission decided in January 2021 to reinforce the monitoring program, asking digital companies that signed the Code to provide more insights and data on the impact of the measures taken, and to include a special focus on fighting Covid-19 vaccine disinformation. In May 2021, the Commission published guidance—COM(2021) 262—on how the Code of Practice on Disinformation28 should be strengthened to become a more effective tool for countering disinformation in the broad sense, that is, including information influence operations and foreign interference in the information 28  https://digital-strategy.ec.europa.eu/en/library/guidance-strengthening-code-­ practice-disinformation. Accessed February 2022.

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space. In particular, the document calls for broadening participation and collaboration among the different actors with tailored commitments; increasing the coverage of fact-checking and providing researchers with increased access to data through the establishment of the European Digital Media Observatory (EDMO); better demonetizing of disinformation linked to ad placements; and empowering users by reinforcing media literacy initiatives, drawing on synergies with the Digital Education Action Plan (2021–2027). In addition, the Commission recommended adopting tailored commitments addressing the use of messaging platforms for the dissemination of political and issue-based ads, in full respect of the General Data Protection Regulation (GDPR) and EU requirements for privacy in electronic communications services. With a view to transparently increasing the number of actors committed to reducing the impact of disinformation, on November 2021, the European Commission welcomed 16 addition potential signatories who joined in drafting the EU’s enhanced Code of Practice on Disinformation.29 In the following months, the relationships between the Europe Commission and digital platforms entered a new phase with the “Digital Services Act,” which updates the European Union’s legal framework by modernizing the 2000 e-Commerce Directive and establishes measures regarding illegal online content, transparent advertising, and disinformation.

4  Conclusions In the framework of public sector communication (Canel & Luoma-aho, 2019; OECD, 2021), this chapter investigated how EU institutions have dealt with the Covid-19 pandemic and with the pervasive spread of online disinformation, implementing specific policies and communication strategies. The adoption of a multilevel governance approach for tackling the Covid-19 information crisis was a crucial aspect of the EU strategies, as was the attention devoted to the multifaceted relationships with digital platforms and online companies, key players in the contemporary communication ecologies. 29  In particular, Twitch, Adobe, Havas, The Bright App, Neeva, Reporters Without Borders, VOST Europe, the Netherlands Organisation for Applied Scientific Research (TNO), Maldita, PagellaPolitica, Demagog, MediaMath, Integral Ad Science, the GARM initiative, Crisp Thinking, and Newsback.

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In this context it is important to focus on several specific implications deriving from the analysis of this complex and fluid scenario. First, the Covid-19 pandemic revealed that in the face of global crises, public responses must be coordinated, while the measures that European institutions introduced to protect Member States and Europe’s citizens demonstrated the need for multilevel policies. This multilevel approach has also been strategically adopted for public communication, in order to spread EU information about the policies and the interventions implemented to tackle the Covid-19 crisis and to defuse disinformation’s effects at the supranational level, against a backdrop of fluctuating distrust toward governments and institutions (Lovari et al., 2020). For the first time, because of the paralysis of individual Member States in reacting to this uncertain scenario, European leaders and institutions energetically imposed their presence on national politics and public opinion, calibrating information and communication flows using a multichannel and multi-actor strategy. In the critical phase, the reassuring communication of the presidents of the European Commission and Parliament was a memorable occasion of European unity and an extraordinary opportunity for the European public communication sector to strategically and transparently impact citizens and the media. Indeed, the provision of and accessibility to accurate sources of verified information were essential in enabling democratic engagement and nurturing trust in European institutions during the pandemic. In this scenario, effective public sector communication that is transparent, respectful of the values of honesty, integrity, and impartiality can play a crucial role in helping to rebuild confidence in governments and institutions (OECD, 2021). Second, the pandemic has shown that disinformation has become a public and political problem that must be critically addressed for the health of democracy in general, and European democracy in particular. Indeed, the disinformation created by the Covid-19 pandemic has reopened the debate on what the European public space is and what it should be in a hybrid media system where digital platforms are increasingly powerful, and information is ever more abundant. The constant overload of false, misleading, and often hostile messages spread on online avenues, often sensationalized and politicized by mainstream media, shows that without effective and integrated counteraction, the health of the Western political system is at stake. Regarding disinformation and information disorder as a public problem has brought these issues to the forefront of international

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agendas and public debate. Thus, the Covid-19 pandemic has accelerated several processes and paved the way to solutions for issues that already figured on the EU institutional agenda at different levels of advancement. The digitized global information system was hard-hit by the spread of Covid-19 disinformation, clearly showing the intertwined and pernicious effects of propaganda by players who have taken advantage of the crisis for their own purposes, whether they were populist, sovereigntist and anti-­ European political voices or real external attacks aimed at destabilizing the European Union’s functions and geopolitical role. Disinformation also intersects—in terms of both language and policy-making—with hate speech. Though the literature often makes a sharp distinction between these two concepts, during crises, they end up overlapping in public and political communication practices, producing a systemic cognitive distortion at the level of propaganda which European institutions have attempted to counter. This is not the first occasion on which the medical and health fields have been targets of conspiracy attacks (Fuchs, 2021), but this time has made it clear that the two phenomena are interrelated and must be tackled together to prevent more negative effects on public action. Third, the anti-misinformation strategy launched in 2015 by the European Union has only recently begun to take effect. Though it is too early to determine what its overall results may be, it has shown its potential in terms of crisis communication in different waves of the pandemic (Coombs, 2020). However, the potential of this strategy has been seen in terms of emergency and crisis communication response (Coombs, 2014). Even if the mechanism was initiated during the Covid-19 crisis and has already produced encouraging results, unfortunately the actions are still not very visible and for now are still mainly a debate for insiders or specialists. Despite the enormous efforts made by EU institutions and their public communication strategies, there is still a wide gap between citizens and institutions. And though the percentage of Europeans who say that they trust the EU has increased during the pandemic and reached its highest levels in more than a decade,30 it is still below 50%. This situation presents an opportunity for EU institutions to have a more central role in determining the shape taken by domestic media coverage and in influencing agenda-­ building dynamics. From a communicative standpoint, the European institutions must strive to keep this advantage, as there is a 30  https://ec.europa.eu/commission/presscorner/detail/en/ip_21_1867. February 2022.

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serious risk that it will be lost in post-crisis management if old equilibria are re-established. The lack of attention to European issues shown before the Covid-19 pandemic (D’Ambrosi et al., 2021) is still influencing the impact of EU public communication, and it should be investigated in future studies in order to see whether the multilevel communication approach to fighting disinformation is also changing citizens and media practices in EU information-seeking. Additionally, disinformation must be addressed as a coordinated and integrated public action on several levels. Regulatory action is crucial, especially if it is coordinated at the macro level and taken together with the different public actors. Regulatory action can, however, be counterproductive if it is not able to integrate professional practices at many levels: journalistic, technological, and communication skills with academic knowledge. In order to be effective, all this requires a strong connection with civil society and the general public. It is also necessary to invest in media literacy and media education for the entire population, not only for the youngest generations. Moreover, constant and coordinated efforts involving public institutions, mass media, and digital companies are essential for creating or strengthening partnerships and joint interventions to tackle this problematic issue at different levels. Scholars have drawn attention to the impact of such collaborations on mitigating the spread of misinformation and reducing polarization at country level. European institutions have provided an interesting case study from this standpoint, since the approval of the Code of Practice in 2018. Partly because of the acceleration brought on by the pandemic, digital platforms are now the connective tissue of contemporary Western societies, since the majority of transactions and services, as well as information and communication processes, take place digitally on the Internet and on participative online avenues. The recent Digital Service Act—proposed in January 2022, but not yet effective until final approval by the European Council—will require digital platforms and online companies to continue to collaborate with governments to stop the spread of problematic information, providing trustworthy content and paying strategic attention to cultural and linguistic factors that could reduce the spread of toxic content that could harm citizens and weaken democratic processes. Now that the platform lobby’s first reactions have already begun to circulate in the European public debate, it will be interesting to investigate how these relationships develop.

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Guo, L. (2014). Toward the third level of agenda setting theory: A network agenda setting model. In T. Johnson (Ed.), Agenda setting in a 2.0 world. New agendas in communication (pp. 112–133). Routledge. Habermas, J. (2015). Democracy in Europe: Why the development of the EU into a transnational democracy is necessary and how it is possible. European Law Journal, 21(4), 546–557. Han, B. C. (2017). In the Swarm: Digital prospects. MIT Press. Helmond, A. (2015). The platformization of the web: Making web data platform ready. Social Media and Society, 1(2), 1–11. https://doi. org/10.1177/2056305115603080 Hermida, A. (2010). Twittering the news: The emergence of ambient journalism. Journalism Practice, 4(3), 297–308. Larson, H. J. (2020). Blocking information on Covid-19 can fuel the spread of misinformation. Nature, 58, 306. https://doi.org/10.1038/ d41586-­020-­00920-­w Lathrop, D., & Ruma, L. (2010). Open Government. Collaboration, transparency, and participation in practice. O’Reilly Media, Sebastopol, CA. Lovari, A. (2020). Spreading (Dis)Trust: Covid-19 Misinformation and Government Intervention in Italy. Media and Communication, 8(2), 458–461. Lovari, A., D’Ambrosi, L., & Bowen, S. (2020). Re-connecting voices. The (new) strategic role of public sector communication after the Covid-19 crisis. Partecipazione e Conflitto, 13(2), 970–989. Lovari, A., & Valentini, C. (2020). Public Sector Communication and Social Media. Opportunities and limits of current policies, activities, and practices. In V. Luoma-aho & M. J. Canel (Eds.), Handbook of public sector communication (pp. 315–328). Wiley Blackwell. Luoma-aho, L., & Canel, M. J. (2020). Handbook of public sector communication. Wiley Blackwell. Macnamara, J. (2017). Creating a “Democracy for Everyone”: Strategies for increasing listening and engagement by government. The London School of Economics and Political Science and University of Technology Sydney, London and Sydney. Retrieved https://www.uts.edu.au/sites/default/files/FASS-­ Research-­Report-­Creating-­a-­New-­Democracy-­for-­Everyone.pdf?no-­cache. Maertens, R., Roozenbeek, J., Basol, M., & van der Linden, S. (2021). Long-term effectiveness of inoculation against misinformation: Three longitudinal experiments. Journal of Experimental Psychology: Applied, 27(1), 1–16. Marks, G., Hooghe, L., & Blank, K. (1996). European Integration from the 1980s: State-Centric v. multi-level governance. Journal of Common Market Studies, 34, 341–378. Martens, B., Aguiar, L., Gomez-Herrera, E., & Mueller-Langer, F. (2018). The digital transformation of news media and the rise of disinformation and fake

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CHAPTER 5

The Practice of Emergency Gatewatching During the First Phase of the Pandemic. An Analysis Through the Tweets in Italian, Spanish, French and German Gevisa  La Rocca, Francesca Greco, and Giovanni Boccia Artieri

1   Introduction Two years have already passed from the first cases of Covid-19 registered at the end of 2019 till date. Looking back to understand how an information crisis occurred (PAHO, 2020) and what strategies citizens have put in place to make up for this lack appears necessary and useful for identifying solutions to be applied in the future. As recent history tells us, on December

G. La Rocca (*) Faculty of Human and Social Sciences, Kore University of Enna, Enna, Italy e-mail: [email protected] F. Greco Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. La Rocca et al. (eds.), Infodemic Disorder, https://doi.org/10.1007/978-3-031-13698-6_5

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31, 2019, China communicated the spread of a cluster of atypical pneumonia of viral origin to the World Health Organization (WHO). Most of the cases had an epidemiological link to the Huanan Seafood market in Wuhan, southern China, a wholesale market for seafood and live animals. On January 23, 2020, the first mass lockdown in history begins in Wuhan. After China, it is Europe that is most affected by the virus and must face it both in the medical and political fields, and in the dissemination of information to citizens. The first European countries to introduce lockdown as a restraining measure are Italy, Spain, France and Germany. As regards Italy, although two cases of coronavirus in Chinese tourists visiting Rome were identified at the end of January; on February 21, 2020, what will be called by media ‘patient zero’ was identified, a 38-year-old from Codogno in the Lombardy Region. Several outbreaks appear in some areas of Northern Italy (Fondazione Veronesi, 2020), and from here the first red zones are triggered for Italy. Shortly thereafter, exactly on March 9, 2020 (D.P.C.M. of February 23, 2020), the first European lockdown will be declared, that is, the Italian one. On March 11, 2020, the WHO officially declares a pandemic status. Starting from these episodes, the virus spreads rapidly throughout Europe, whose member countries, like domino cards, fall one at a time under the grip of Sars-Cov-2. From here, containment measures begin to be adopted against the spread of the virus, which unequivocally mark this period. In the absence of clear scientific information (Lovari, 2020) capable of stemming the pandemic, what politics had the opportunity to operate was a reduction in interpersonal contacts identified as the main mode of contagion. In Spain, the lockdown was introduced with the ‘Real Decreto 463/2020’ of March 14, 2020. In France the lockdown was introduced with ‘Décret n. 2020-260’ of March 16, 2020. A turning point towards the adoption of the restrictive measures for Germany takes place on March 12, 2020, when the Minister of Health bans gatherings between more than 1000 people (RFI, 2020), on March 13, 2020 11 of the 16 Länder decided to close the schools and universities starting March 16. On March 16, 2020, the German federal government enters into an agreement with all the Länder, that is, the individual states that make up Germany, on the guidelines to follow to combat the spread G. Boccia Artieri Department of Communication Sciences, Humanities and International Studies, University of Urbino Carlo Bo, Urbino, Italy e-mail: [email protected]

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of the coronavirus. On March 22, 2020 the measures become more stringent and will remain in force for at least two weeks (AGI, 2020). These four countries are not only the first to apply restrictive containment measures against the spread of the pandemic, that is, to make the choice of temporary lockdown, but they represent different types of information resilience in terms of differences in news media and political communication, according to the well-known Hallin and Mancini (2004) model. In particular, a recent study (Humprecht et al., 2020) analyses the structural conditions of several countries that influence information resilience and that concern the factors of the political environment—such as the degree of polarization of society and the populist communication—the factors of the media environment—such as low trust in news, weak public service media, and more fragmented, less overlapping audiences—the factors of the economic environment—the size of the media market and the rate of use of social media. Although the study focuses on the level of resilience to online misinformation, the ranking of countries that the framework identifies shows us that Spain and Italy are characterized by a low level of information resilience, while France has a medium level and Germany a high level. This shows how these countries indicate a different approach to the production and consumption of information that highlights collective characteristic that transcends the individual level (Table 5.1). Analysing the tweets related to the pandemic in Italian, Spanish, French, German of the period immediately preceding the first of the European Table 5.1  Timeline of the main events of March 2020 in the four countries Country Major Event Timeline Italy

March 4, 2020, first press conference of the past premier Giuseppe Conte, that announces the closure of schools and universities, then—in another press conference—he announces the national lockdown starting from March 9, and on March 24, he announces the first extension of the lockdown. Spain The Spanish government, in the extraordinary session on Saturday March 14, 2020, declared a state of emergency, thus decreeing the imposition of the national quarantine (Cué, 2020). The measure, which entered into force the same day, was introduced to reduce the number of infections. French March 16, 2020, the lockdown is decreed and takes effect from 12 a.m. of March 17, it is a lockdown very similar to the Italian one. German March 16, 2020, the German federal government announced that it had entered into an agreement with the Länder on the guidelines to follow to combat the spread of the coronavirus. On March 22, 2020 the measures became more stringent (AGI, 2020).

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lockdowns (between March 4 and 11, 2020) will allow us to observe the feelings experienced, to analyse the reflections carried out in those first hours and to investigate the discussion topics of those who saw the Covid-19 spreading in their daily reality. It will also allow us to understand how, starting from the first Italian cases and the lockdown introduced by Italy, the other three European countries have begun to prepare for the impact of the first wave of the pandemic. The four languages—representing the four countries—are also spoken outside their national contexts, due to migration or colonization stories. In this way, in addition to providing us with information on the four European countries, this analysis gives us the opportunity to trace the dynamics of the public debate on what is happening in Europe—inside and outside its borders—in relation to the dissemination of Covid-19 and the policy choices that are being made by target language communities in other non-European countries.1 Thus, this set of linguistically selected tweets will allow us to answer the following research questions:

1  Indeed, Spanish is the official language of many states of South America. French is spoken in Canada (i.e., mainly in the provinces of Québec and New Brunswick and to a significant extent in Ontario and Manitoba), Belgium, Switzerland, numerous islands of the Caribbean and the Indian Ocean, Luxembourg, the Principality of Monaco, is the official language of about 30 states worldwide (as a legacy of the French colonial empire and Belgian colonization), numerous international organizations (e.g., the United Nations Organization), is one of the three working languages (together with English and German) of the EU, and it is also spoken, protected, and enjoys a co-official status (with Italian) in the Aosta Valley, Italy. Finally, Italian is the official language in San Marino, Switzerland, and the Vatican City, in parts of Croatia and Slovenia, and there are Italian language communities that can be found in states such as Albania, Argentina, Australia, Belgium, Bosnia, Malta, Egypt, Eritrea, other European States, Africa, the United Kingdom, and the United States of America. The German language in Europe is spoken and recognized as an official language in Germany, Austria, Switzerland, Liechtenstein and Luxembourg. It is the language with the largest number of native speakers on the European continent and the European Union. Liechtenstein is the only country in the world where German is the only official and spoken language. Outside these states, there is a special statute in the Italian territories of the autonomous province of Bolzano. In the rest of Europe, German is mainly spoken as a second language. Other German-speaking European communities are found in northern Italy, in the French regions of Alsace and Lorraine and in some border centres in the county of southern Jutland in Denmark. German-speaking communities can also be found in parts of the Czech Republic, Slovakia, Hungary, Poland, Romania, Serbia, Russia, and Kazakhstan.

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[RQ1] What kind of information is disseminated in the early period of the pandemic through Twitter? What kind of sentiment is associated with them? [RQ2] What communicative practices were used by public opinion to theme the pandemic in this early phase of virus spread? To answer these research questions, we use Twitter as an observation point and we follow the flow of tweets in Italian, Spanish, French and German linked to the hashtag #Covid-19, on which a merged method is applied (Gobo et al., 2021) to Emotional Text Mining (Greco, 2016a), in order to extract content and sentiment from tweets.

2   Literature Review The research questions that guided this study are based on the use of Twitter as a place for public discussion and the use of hashtags during times of crises. There is a lot of established literature on these two issues. Many recent studies analysing Twitter contents have helped to delineate its role in monitoring public debate. Among the first works that analyse how Twitter can be considered a tool for analysing social event is the book Twitter and society by Weller et al. (2014). This work highlights how, in terms of interpersonal communication, the platform has become synonymous with microblogging in most countries and is increasingly used as a source of real-time information and a place for debate in news, politics, business, and entertainment, in this sense “the breadth and diversity of these uses of Twitter in contemporary society document the considerable adoption of Twitter as a platform for everyday and extraordinary, personal, and public communication” (Weller et  al., 2014, p. xxxvii). As Burgess and Baym (2020) point out, the further evolution of Twitter over the past decade has meant that we are faced with the transformation from a technology to a society and a culture. Namely, Twitter has become a place where history and culture are not only recorded but written in real time. Twitter hashtags (i.e., bottom-up user-proposed tagging conventions) have played a key role in this process, with the hashtag innovation proposed by Twitter serving as the embodiment of user participation owing to it being related to information organization tasks (Chang, 2010). Further, the use of hashtags and Twitter have contributed to spreading activism and participation regarding political and social themes (e.g., Rambukkana, 2015; Dobrin, 2020). Indeed, the use of

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hashtags has become increasingly relevant in Twitter: they have passed from being thematic aggregators to becoming polysemic collectors that aggregate people’s emotions. Alongside the hashtags, over time, other features have been adopted to develop and monitor the public debate. In Twitter, features are represented by mentions (@), quotations, retweets (RT), uploads inside the tweets (i.e., links, photos, images, emojis). @mention or @reply have become a key feature of Twitter as a tool for conversations and socializing, and usage allows the creation and maintenance of networks between users. “Retweeting created visibility, followers, and amplified attention” (Burgess & Baym, 2020, p. 92). It is this recirculation of messages, this visibility combined with the use of hashtags that we need to understand, and that why working on these platforms, analysing these public spaces that are open to peer discussion, has become fundamental to monitor the emergence of trends with respect to public agenda that revolves around issues of public interest and follow its evolution. As Bruns and Stieglitz (2012) explain, a large number of retweets occur when there are natural disasters or crisis events (Bruns & Burgess, 2015), and they fall largely into a category best described as “breaking news” or “rapid information dissemination.” A high number of retweets can be attributed to a specific conversational practice on Twitter, the gatewatching (Bruns, 2005). It is an activity produced by citizens in real-time for disseminating, sharing, and commenting on news that originates from media outlets on social media platforms in case of acute events that generate an ad hoc community. Therefore, events produce a high percentage of retweets and events/hashtags that do not generate an online conversation flow (Bruns & Stieglitz, 2012). Depending on the theme, Twitter users adopt different conversational and relational models. It can be argued that “these distinctly divergent and stable patterns in user activities for different hashtag use cases indicate the existence of various conceptualizations by users of the hashtag community that they are either seeking to address or participate in” (Bruns & Burgess, 2015, p. 21). Bruns and Stieglitz (2012) argue that hashtags linked to a crisis event, or a television program (topical hashtags) are much more likely to induce information sharing that, in turn, engages and disseminates other information conveyed by URLs, photographs, and continuous retweets, compared to what occurs in the case of hashtags with generic content and meaning (i.e., not topical hashtags). The conscious use of hashtags and features is affirmed on Twitter, to the point of developing capacity for collective action on specific topics/

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events. Regarding acute events, these studies assume that the onset of crises or disastrous events will naturally accompany Twitter hashtags about the events, mostly owing to the need of Twitter users related to sharing information, following and commenting news, using the hashtag as a common gathering place in order not to disperse the flow of information (e.g., Bruns & Burgess, 2012, 2014; Bruns et al., 2012). Given these premises, it is not surprising that from 2020 to 2021 have proliferated numerous studies dealing with hashtags related to the pandemic, with #coronavirus and #covid-19  in the lead. Like Raghav Rao et al. (2020) reported, the flow of tweets related to covid-19 has grown exponentially and in step with the spread of the virus. The analysis shows that there are three main issues for which citizens are looking for information: the virus contagion, the prevention, and the economic impact. In consideration of this interest in the topics addressed within Twitter and the usefulness of their extraction and analysis, various tweets collection projects were born. For example, the one of Aguilar-Gallegos et al. (2020) that built a dataset of 8,982,694 Twitter posts around the coronavirus health global crisis, for the period from January 21 to February 12, 2020, collecting multilingual tweets, prevailing English, Spanish, and Portuguese, using the hashtag #coronavirus. Or the project proposed by Kabir and Madria (2020), named “CoronaVis,” which is a data analyser and data repository using a live application to observe in real time tweets on Covid-19 generated in the USA. The aim of this project is to use tweets (as user-shared data) in order to enable researchers to visualize topic modelling, study human subjectivity, and to model human emotions during the Covid-19 pandemic. Indeed, research has depicted very clearly that the importance of Twitter and its hashtags has grown during the Covid-19 pandemic. An example of this are the several studies that have dedicated themselves to analysing the social effects of the pandemic through hashtags. These are studies that have taken as observation points, now a specific hashtag (e.g., Bhat et al., 2020; Boccia Artieri et al., 2021a, 2021b; Kurten & Beullens, 2021), now hashtag chains (e.g., Manguri et al., 2020; Kausar et  al., 2021, Petersen & Gerken, 2021). These studies also worked on tweets in different languages, such as Belgian, Arabic, English, and so on. In our study, we instead selected the hashtags in different languages (Italian, Spanish, French, and German), using a unique hashtag for data collection: #Covid-19, in order to expand the findings of the work of La Rocca and Greco (2022).

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3   Method The literature review showed that Twitter is a platform used socially for real-time information and public discussion—particularly in the face of acute events and crises—and that social research analyses what happens in conversations on the platform to measure the cultural ‘temperature’ on different public issues. He also highlighted how the use of hashtags on the platform allows, on the one hand, users to voluntarily aggregate conversations on specific topics and react to them (through likes, mentions, comments, and shares)—showing “the role of the Twitter hashtag as a means of coordinating a distributed discussion among large numbers of users, who do not need to be connected through existing follower networks” (Bruns & Burgess, 2012)—and, on the other, researchers to collect and analyse this wealth of arguments and relationships. The importance of hashtags for this type of analysis has fruitfully led scholars to analyse them in the context of the Covid-19 pandemic. Based on hashtag studies, we can refer to the hashtag #Covid-19 as a “topical” hashtag that aims to aid the visibility and discoverability of Twitter messages, and since this is especially important in a crisis context. Bruns and Burgess (2015) showed that there are differences between hashtags based on the flock of retweets and URL embedding that the hashtags themselves can generate and that depend on the event from which they originate. In this sense, a hashtag with high percentages of retweets/mentions is defined as a topical hashtag, “used for the rapid formation of ad hoc issue publics, gathering to discuss breaking news and other acute events” (Bruns & Burgess, 2015, p. 2). We are therefore faced with the formation of an ad hoc community that is generated around the hashtag and that does not consider the structural characteristics of the users (i.e., gender, age, income level) nor whether they belong to the same social graph. The topical hashtag we used, #Covid-19, was generated by an acute event and conveyed by the media; owing to these characteristics, we can define it as a hybrid form of hashtag because, undoubtedly, the first wave of the Covid-19 pandemic had news related to it conveyed by TV and mainstream media (e.g., Boccia Artieri et al., 2021b), making it a media event per se. This may explain the high percentages of retweets in all four languages and would identify conversational practice activated within the Twittersphere as gatewatching (Bruns, 2005). Based on Bruns and Stieglitz (2012, p.  7), we used yourTwapperKeeper (see also Bruns &

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Liang, 2012), which utilizes Twitter streaming Application Programming Interface (API) and search API functionality to capture, in real time, any tweets containing the keywords or hashtags selected by the researcher (i.e., #Covid-19). Complying with Twitter’s Standard Search API policies/parameters, we downloaded the tweets downloaded daily using the rtweet package of R statistics, version 0.7.0 (Kearney, 2020). Following the indications of Bruns and Stieglitz (2013, p. 93), we describe the metrics about user activity within the #covid-19 hashtag dataset. As scholars suggest—in Table 5.2 section a—have been reported the values ​​for: (1) the original tweets sent ‘tweets which are simply original statements, without mentioning other users’; (2) the second information contained in the table is the total number of retweets (RT); (3) the RTs were subsequently divided into @replies sent, which constitute @mentions sent that are ‘tweets which contain “@user,” but no indication that the message is a retweet of an earlier post by user’; (4) and RT plus @mentions, which represent ‘tweets which are in the format “RT @user [original message]” Table 5.2  Descriptive characteristics of the dataset from March 4–11, 2020 Italian tweets

Spanish tweets

(a) Description of the dataset for the topical hashtag Original tweets 112,503 161,056 (16.3%) (12.6%) Retweets (RT) 824 7552 (0.1%) (0.6%) @replies sent 33,865 61,307 (4.9%) (4.8%) Retweets and @mentions 542,322 1,050,817 (78.7%) (82.0%) Total amount of tweets 689,514 1,280,732 (100.0%) (100.0%) URL 174,662 319,026 (25.3%) (24.9%) Tweets geolocation 5852 2791 (0.9%) (0.7%) (b) Description of lexicometric measures for corpora Type 103,601 145,343 Token 18,760,987 35,235,705 Type Token Ratio (TTR) 0.006 0.004 Hapax 35,608 47,849 Hapax% 34.4% 32.9%

French tweets

German tweets

68,941 (8.4%) 536 (0.1%) 30,329 (3.7%) 722,108 (87.9%) 821,914 (100.0%) 176,631 (21.5%) 1658 (0.3%)

45,190 (20.04%) 49 (0.0%) 17,117 (7.7%) 159,690 (71.9%) 222,046 (100.0%) 77,158 (34.7%) 1206 (0.5%)

76,089 24,504,338 0.003 23,350 30.7%

81,514 5,504,245 0.015 30,395 37.3%

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or equivalent’; (5) the total number of tweets making up the dataset for each of the four groups; (6) and we have also added URLs that provide an ‘indication of the amount of external resources a user is introducing into, or retweeting from, the hashtag conversation’; (7) as a final information, geolocation was reported for a small percentage of tweets. Within the retweets group, we did not distinguish between ‘unedited retweets sent’ and ‘edited retweets sent’. Furthermore, as Bruns and Stieglitz (2013, p. 94) already suggest, we know that these web-scraping operations contain margins of error, which may depend on ‘temporary interruptions may cause gaps in transmission which even a secondary check through the search API cannot fill’. However, this information allows us to hook the content and sentiment of the tweets to the conversational practice activated by users and to begin investigating our research questions. Moreover, hereinafter, we will be referring to tweets by language (not country) because we know that languages can be spoken outside national borders, and we could not all geolocate the tweets. In fact, as Table 5.2 reports, only a very low percentage of tweets have been geolocated. This is a percentage that for the four countries fluctuates between 0.3% and 0.9%. However, we assume that the tweets can comprehensively depict these four societies at that time. Based on previous studies (Boccia Artieri et al., 2021a, 2021b), we decided to apply Emotional Text Mining method (ETM) to data on the chosen hashtag (Greco, 2016a; Greco & Polli, 2020). Owing to its characteristics, the ETM is a merged method (Gobo et al., 2021; La Rocca et  al., 2021), merging quantitative and qualitative techniques. We chose to use ETM for several reasons. First, ETM is based on a socio-constructivist approach, allowing for the semantic and semiotic contents conveyed by the text to be identified; this is operationalized by detecting the lexical profiles characterizing the hashtag and its symbolic aspects, both of which are relevant when attempting to explore public perceptions (Greco & Polli, 2021).2 Second, ETM is used for conducting a context-sensitive text mining approach on unstructured data—which 2  ETM is a sentiment analysis that allows for a social profiling. This new analytical method was developed by Greco at Sapienza University of Rome jointly with Paris Descartes University from 2011–2015, being awarded by the University of Sorbonne Paris Cité and the Sapienza University of Rome. For an in-depth understanding of the ETM method, both regarding its theoretical and methodological background and statistical procedures, we suggest referring to Greco’s studies (e.g., Greco, 2016a, 2016b; Greco & Polli, 2020). ETM has recently been incorporated into merged methods (Gobo et al., 2021).

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constitutes 95% of big data (Gandomi & Haider, 2015)—and is suitable for analysing social media-based communication (Greco & Polli, 2020). Third, ETM uses an unsupervised bottom-up approach, making it suitable for the multilanguage corpora, allowing for comparing large size corpora in different languages, not being limited by the existence of a dictionary, and maintaining the semiotic and semantic meanings conveyed by the language (Greco, 2016b), the latter two being the expression of a specific culture (Vygotskij, 2010). For our data analyses, we have conducted the following steps for each language: 1. We cleaned the messages (i.e., removing the links, emails, emojis, and emoticons) and kept only the text. 2. We removed retweets from the corpora and owing to message production differences by language (Table 5.2b), we adopted a different document selection procedure for each language. This was aimed at obtaining comparable corpora, with one for each language. We selected all messages in the French language (n = 99,270), those with more than 9 words in the Italian language (n = 99,892), and a random sample of 99,000 Spanish messages. 3. We calculated two lexical indicators, the type-token ratio (TTR) and the percentage of hapax (H) (see Table 5.2b), to check for the possibility of using ETM (Giuliano & La Rocca, 2010). These indicators are used in linguistic statistics to determine the lexical richness of a text. The TTR is the ratio between word tokens and word types. The hapax legomena were words that appeared only once in the text. 4. Each corpus was lemmatized, filtering out stop words, the term “Covid-19,” and terms with a low rank of frequency to reduce the matrix-dimension (Greco & Polli, 2020). 5. We performed a cluster analysis on the term-document matrix with a bisecting k-means algorithm based on cosine similarity limited to 20 partitions, excluding all the tweets that did not have at least two co-occurrences (Savaresi & Boley, 2004; Steinbach et al., 2000). 6. To choose the optimal solution, we calculated the Calinski-­Harabasz, the Davies-Bouldin, and the intraclass correlation coefficient (ρ) indices (Greco & Polli, 2020). 7. We performed a correspondence analysis on the term-cluster matrix (Lebart & Salem, 1994). Since the factors had the same terms ordered differently according to the absolute contribution value, to

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interpret a factor, we considered only terms with the highest absolute contribution value in the factor and excluded them from the other factors in which they have a lower value (Greco, 2016a). This allowed us to identify the culture’s symbolic categories framing the cluster in a symbolic space of sensemaking. 8. The interpretation process proceeded from the highest level of synthesis (correspondence analysis results) to the lowest one (cluster analysis results), assigning labels to factors and clusters (i.e., proceeding from the semiotic to the semantic level). After interpreting the results of each corpus, we compared them and redefined3 the labels in order to highlight similarities and differences in Covid-19 representations between languages (see Tables 5.3, 5.4, 5.5 and 5.6). 9. The sentiment was calculated according to the number of messages classified in the cluster and its interpretation (Greco & Polli, 2020).

Table 5.3  Cluster analysis and correspondence analysis results and sentiment description for Italian tweets Cluster Tweet

Tweet %

Label

Sentiment Factor 1

Italian

Factor 2

Factor 3

Contagion Reaction Categories

1

23,717 29.5

2 3

18,780 23.3 19,332 24.0

4

18,740 23.2

Forced confinement Italian lockdown Foreign threat of contagion National Threat: the Red Zone

Negative

Sensibility

Time

Negative Negative

Sense Policy Sensibility

Space

Negative

Sense

Health

3  The classification procedure was completely automatic, but the researcher did have the possibility to assign names of labels, thus ensuring that the content that emerged from the analyses were reflective of the data set and respected the original information. Thus, while the software automatically classifies the terms and builds clusters, the researcher identified their meaning by enclosing them in a label.

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Table 5.4  Cluster analysis and correspondence analysis results and sentiment description for Spanish tweets Cluster Tweet

Tweet %

Label

Sentiment Factor 1 Factor 2

Spanish 1 2 3

10,839 11.7 9854 10.6 11,521 12.4

4 5

10,218 11.0 17,989 19.4

6 7

13,339 14.4 9821 10.6

8

9090

9.8

People panic Spanish lockdown Prevention information Economic impact World pandemic spread Global health impact Individual prevention strategies Countries forced confinement

Factor 3

Spread

Crisis

Level

Negative Negative Neutral

Local

Health

Negative Negative

Local Global

Economic Micro Micro

Negative Neutral

Global Local

Health

Negative

Local

Macro Health

Macro Micro Macro

Table 5.5  Cluster analysis and correspondence analysis results and sentiment description for French tweets Cluster Tweet

Tweet %

Label

Sentiment Factor 1

French

Impact

1

12,630 14.3

2 3 4

11,514 13.0 9544 10.8 8540 9.7

5

16,462 18.6

6 7

9532 9745

8

10,471 11.8

10.8 11.0

French contagion National crisis Italian lockdown National psychoses World pandemic spread French lockdown Economic impact Individual prevention strategies

Factor 2 Factor 3 Level

Negative

Crisis Health

Negative Negative Negative

Productivity Macro Social Macro Productivity

Health

Negative

Social

Micro

Economic

Negative Negative

Macro Productivity Macro

Health Economic

Neutral

Productivity Micro

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Table 5.6  Cluster analysis and correspondence analysis results and sentiment description for German tweets Cluster

Tweet

Tweet Label %

Sentiment

German 1

12,597

13.6

2

9288

10.1

3

13,045

14.1

4 5

12,199 11,811

13.2 12.8

6

10,486

11.4

7

10,368

11.2

8

12,535

13.6

Factor 1

Factor 2

Factor 3

Impact

Contagion

Reaction Sensibility

Government reaction Sport events cancellation Italian lockdown People panic Global infection spread Health impact

Negative

Health

Active

Negative

Social

Active

Neutral

Health

Negative Negative

Negative

Economic impact Social event cancellation

Positive Neutral

Sense

Passive

Sensibility Health

Passive Passive

Health

Active Sensibility

Social

Passive

Factor 7

Exaggerate

Reasonable

Sense

4  Data Analysis The purpose with which we develop this path of analysis is to find an answer to our two research questions: (1) to define the type of information that spreads in the first period of the pandemic trough Twitter and the sentiment associated with them [RQ1] and (2) to identify communicative practices used by public opinion to theme the pandemic in this early phase of virus spread [RQ2]. To answer these questions through data analysis we proceed by tracing the salient elements in the four groups of tweets and subsequently, in the section dedicated to the conclusions, we reconstruct the picture of the results found, providing an interpretation according to the research questions. Given that it was not possible to geolocalize the tweets, in the analysis of the data, attention is paid to tracing those elements that are attributable to the national level and those that instead pertain to a supranational level; in this way, we try to identify which themes pertain to one level and which themes pertain to the other level and which sentiment is associated with them.

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4.1   Analysis of Italian Tweets A first result emerging from the analysis of Tweets in Italian is a symbolization of the Covid-19 pandemic along three main dimensions: contagion, reaction, and space-time dimension (Fig. 5.1). The first factor (43.3% of inertia) distinguishes two opposite ways to perceive the contagion: to face the emergency using rationality (negative pole) or sentiments (positive pole), with the latter being mostly driven by emotional reactions (i.e., fear). Italy is the first European state to be hit by the virus, the attention of Italians and Italian politicians is all turned to facing an external enemy. Unsurprisingly, people’s first reaction to the Covid-19 pandemic threat was to fight/flight, an automatic and physiological reaction to an event perceived as stressful/frightening. While rationality helps to prepare for a fight, emotional (i.e., negative emotions) assists to prepare for flight. The second factor (35.2% of inertia) reflected the reactions: distinguishing the political reaction (negative pole), which is aimed to face the Covid-19 pandemic threat, and monitoring health (positive pole), which is aimed at dispatching the daily news on the spread and victims of Covid-19. The third factor (21.5% of inertia) sets the space-time dimension of the Covid-19 pandemic spread: while one pole focused mostly on the geographical spread of the virus (negative pole), the other reflected its time progression (positive pole).

0,5 TIME 4_NATION_THREAT

-0,53_FORCED_THREAT

0,0

0,0 -0,5

0,5

Z Axis

Y Axis

INTERVENTION

-1,0

REACTION

POLITICAL

2_LOCKDOWN

1_FORCED_CONFIN

-0,5

SENSIBILITY

0,0

0,5

SOCIAL

SPACE SENSE

X Axis

CONTAGION

Fig. 5.1  Symbolic space emerging from the Italian corpus

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In this Italian symbolic space, each cluster was explained only by two factors; research shows that this specific configuration of the factorial space tends to be found when people’s lives are in danger (Greco, 2016b). It may be that keeping reason and emotion distinctively separated helps people in coping with threats by enabling them to think rationally while feeling frightening emotions; based on Boccia Artieri et  al. (2021b), this distinction can be detected when, in the text, words associated with rational thinking are not associated with emotional ones, and vice-versa. Interestingly, the Italian messages were set by a limited number of symbolic dimensions while, as we shall see later, the Spanish and French ones presented a larger set of them (see Figs. 5.2 and 5.3). Since symbolic categories describe adaptive behaviours (Fornari, 1979), when people feel in danger, they tend to use a reduced set of them (Greco, 2016b). The reason explaining this difference may owe to the Italian past Prime Minister Giuseppe Conte’s announcement of the Italian lockdown on March 4, 2020, a time when the plans of the two other countries were still under formulation owing to them being in different stages of the spread of Covid-19 and having diverging perceptions about its danger. As aforementioned, Italy was the first European country that enforced lockdown measures. In the first stages of the lockdown, the perception of threat from Covid-19 was so intense that Italians totally delegated the

SPANISH_LOCKDOW

Y Axis

CRISIS

-1,0

WORLD_PAN_SPREA

MACRO

COUNT_FORC_CONF

0,5

PREVENTION_INFO PEOPLE_PANIC

-0,5

0,0

0,0

IND_PREV_STRAT

-0,5

0,5

MICRO

-0,

IMPACT X Axis

Fig. 5.2  Symbolic space emerging from the Spanish corpus

5

0,0

1,0

GLOBAL

0,5

HEALTH 1,0

LEVEL

ECONOMICS

1,0

ECONOMIC_IMPACT

LOCAL

Z Axis

GLOB_HEALTH_IMP

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FRENCH_LOCKDOWN ITALIAN_LOCKDOW WORLD_PAN_SPREA

IND_PREV_STRAT NATION_PSYCHOSE

1,0

NATIONAL_CRISIS

0,5

-0,5

ECONOMIC_IMPACT

-1,0

LEVEL

Z Axis

CRISIS

0,0

Y Axis

0,5

MICRO

FRENCH_CONTAGIO

HEALTH

113

0,0

ECONOMIC ,0 1 -

-0,5

PRODUCTIVITY

1,0

X Axis

0,5

IMPACT

MACRO

,5

-0

0,0

SOCIAL

Fig. 5.3  Symbolic space emerging from the French corpus

government to the management of the health crisis and to solve the emergency, giving up their personal freedom (Boccia Artieri et  al., 2021b); nonetheless, this delegation was partially withdrawn in later stages (Boccia Artieri et al., 2021b). Unsurprisingly, the sentiment was overall negative for Italians (see Table 5.3). Within Italian clusters, instead, we could distinguish elements exclusive to Italy and the supranational context represented by Europe and China. The “forced confinement” (cluster 1) arose from national governmental choices (i.e., the introduction of the containment measures as a result of the Prime Minister’s decrees) and its echo in the tweets is likely linked to the social communication campaigns activated by the Ministry of Health and the Department of Civil Protection, named “Leave the virus out the door,” which linked the hashtag #iorestoacasa to its launch (#stayathome). This hashtag was repeated 4211 times within the tweets classified in this cluster. Tweet cl-1 (forced confinement): homework: take any notebook out and fill it as usual, but with this sentence: I have to stay at home, I have to stay at home, I have to stay at home, I have to stay at home, I have to stay at home, let’s stay at home (score = 51,591.23).

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Because they were forced to stay indoors, Italians dedicated themselves to “watching” (485) “TV” (437). This activity is also reported within the next cluster, “Italian lockdown” (cluster 2), where it appears as a “rewatching” (106) of “programs” (105). Nonetheless, watching TV did not seem to turn off Italians’ minds, as within this cluster, an important awareness emerges among Italians, linked to the “economy” (273) and the difficulties that they will face because of the crisis produced by the Covid-19 pandemic. Here, we also begin to find the expectation of a “response” (172), a “support” (190) from the “EU” (176). Tweet cl-2 (Italian lockdown): Much more will be needed, but it will soon also be evident in other European and nations worldwide. The emergency engulfs the economic, decree, more resources for health; the government aims for billions (score= 2982.68175). The Italians have already become aware about the consequences of the Covid-19 pandemic and, concomitantly, they already imagined that they will not be the only ones facing this, as Europe and the world will also be facing these consequences. The alternation between the national and the supranational dimensions can also be seen in the other two clusters. In cluster 3, “foreign threat of contagion,” the external dimension appeared in the identification of the enemy, as people perceived the need to preserve themselves from the invasion of a foreign threat. Accordingly, this is where the words start to appear: “fear” (535), “Chinese” (527), which become the “problem” (481), for which “rules” (459), “responsibility” (416) is needed, to save the “health” (401) and the “economy” (378) from the “crisis” (375). The perception of being unable to defend oneself from the contagion seems to have evoked anger and helplessness in Italians, but it also introduced the possibility of starting to care for one’s family, home, and being obliged to remain with one’s family in own home, as well as to rethink the economy and the nation. Further, this was deemed as a sort of “break,” a break from the known world, a suspension that was suitable for people to reflect. Tweet cl-3 (foreign threat of contagion): they told us, hug a Chinese, eat Chinese food, as they are not the virus. We are all Chinese now among us Italians, as we cannot even shake hands anymore. Coronavirus madness (score= 5851.40). In cluster 4, “national threat: the red zone,” the Covid-19 pandemic is considered as a national threat, placing the spread of Covid-19 within the nation’s walls and leading to the consequent need to identify and demarcate the Red Zones. This is the time when Covid-19 takes hold of the country. The “positive” (2899) “cases” (2123) become a tangible sign

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that the Covid-19 pandemic has reached Italy. Thus, this represents the passage from a threat that was perceived as being outside the national border, linked to the events in China, to an internal and visible threat represented by the cases of “Lombardy” (2185) and “Veneto” (410). The echo of this emerges from the words “therapy” (896) and “intensive” (845). Tweet cl-4 (national threat: the red zone): ICU patients increased because of new infections; health balance of healed and deaths for tomorrow, and evaluation of other red areas. Latest news (score= 21,140.42). Ultimately, we can emphasize that the Italian tweets have four clusters revolve around the element of confinement. The information that citizens are looking for is linked to the advent of confinement, they find themselves in the midst of the pandemic storm and turn their gaze to what is happening in national borders looking for answers and help from the supranational level. 4.2   Analysis of Spanish Tweets The lockdown in Spain is announced a couple of days after the Italian one. Meanwhile, the rest of the world has got to observe what is happening in Italy and how the country is coping with it. In the Spanish language, Twitter users symbolized the Covid-19 pandemic by three main dimensions (Fig. 5.2): spread of contagion (24% of inertia), the crisis (18% of inertia), and the level of the intervention (16% of inertia). The first factor in Spanish symbolizes Covid-19 both regarding the related interventions and sense of emergency. The Spanish focused on the distinction between global and local outcomes. Namely, the first factor distinguished the global spread of the virus (positive pole) and its national spread (negative pole). The second factor distinguished the economic crisis (negative pole) from the health crisis (positive pole), and the third distinguished interventions at the micro (negative pole) from those at the macro level (positive pole). The Spanish corpus shows a higher neutral sentiment (21%; Table 5.4). Even if the Spanish lockdown started on March 14, 2020 (i.e., two days before that of the French), non-essential workers were ordered to remain at home only two weeks later, on March 30, 2020 (Marcos, 2020). Thus, it seems that, the Spanish reaction was the slowest and the adoption of the restriction measures was more gradual; hence, apparently, the more the

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sentiment was negative, the faster was the adoption of the restriction measures. For Spanish tweets, we observed the clusters “prevention information” (cluster 3) and “individual prevention strategies” (cluster 7), which signalled the preparations for the arrival of Covid-19. Remarkably, we decomposed such preparations in two levels: primary-individual and secondary-supra-individual levels. Inside cluster 3, the words that took on a greater significance were “prevention” (2064), “health” (3513), “information” (1626), “protocol” (579), and “Ministry” (583). Tweet cl-3 (prevention information): We met with the different departments of the institution to coordinate measures and actions before the arrival of the coronavirus in our country, reinforcing the prevention and containment measures of this virus (score= 3623.3846). Hence, cluster 3 depicts how people were preparing to cope with Covid-19 since its arrival seemed inevitable, although they had the ability to look at Italy’s status and have a few days of advantage. In fact, it was recommended to follow preventive measures to avoid the collapse of health facilities. The measures to contain the spread of Covid-19 were, of course, declined at the level of individual strategies (cluster 7), such as “washing” (1057) “hands” (2941), “sneezing” (356) inside the elbow, avoiding “handshakes” (207), wearing “masks” (542), and maintaining a physical distance of at least one meter from each other. These measures of protection for oneself and others are all based on the guidelines of the WHO. Tweet cl-7 (individual prevention strategies): Hand washing, sneezing inside the elbow, are actions that reduce the risk of contagion of respiratory diseases. If possible, avoid crowds and close contact with other people when you have the symptoms of flu (score= 6236.0296). The risk associated with the Covid-19 pandemic was generally contained in two cluster: “people panic” (cluster 1) and “global health impact” (cluster 6). They distinguish the primary-local level of risk from the secondary-global one. Tweet cl-1 (people panic): I went to the doctor today because I have been with a cold for a month and a half and I still have a stuffy nose, and maybe my doctor asks me if I have travelled. Then, I will say, “no,” and his answer will be “ahh thank goodness.” The covid run and it is not a simple flu (score= 6236.03). In “people panic” (cluster 1), the “panic” (486) is concentrated on the possibility of contracting Covid-19 and on contact with other “people” (1772), who are now seen as a Covid-19 vectors. Thus, “people panic”

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(cluster 1) is marked by actions that follow the appearance of Covid-19, about which people “talk” (833), owing to which people saw the need to “leave” (802) their work activities and to “think” (399) about what to do, and which concomitantly evoked “hope” (425), despite all happenings. Nonetheless, people also talked about how Covid-19 was spreading fast, coming from “China” (2048), and there was already a second case in “Italy” (4611). Tweet cl-6 (global health impact): an old man who returned from the north of Italy in March is hospitalized at the clinic. Coronavirus second case (score= 885,332). In “global health impact” (cluster 6), we begin to connect the global and local dimensions, with the latter being represented by “Spain” (2868), as well as the following words start to appear: “quarantine” (1823), “nation” (2396), “dead” (958), and “infected” (1132). With the reports on the first Italian red zone, “Lombardy” (276), Italy also appeared in this cluster. Some names of Italian personalities also appeared, such as the past President of the Council of Ministers, Giuseppe “Conte” (91) and—close to the last positions—Angelo “Borrelli” (10), who was the head of the Italian Civil Protection. We also observed the words “France” (460), “Europe” (343), and a “flight” (359) that connects the “south” (240) and the “north” (200). We also can start to see the dimensions related to “risk” (459). The local and supranational dimensions were seemingly and inevitably intertwined when we investigated the “economic impact” (cluster 4). Words and phrases such as the “pandemic” (3274), being “worldwide” (1963), and the “WHO” (1783) taking care of the situation. Tweet cl-4 (economic impact): now, the coronavirus is declared as a pandemic by the World Health Organization (score= 9119.8506). In “economic impact” (cluster 4), we can see the onset of concerns about what is certainly a “crisis” (1824), which is also connected to “oil” (832) and influences the “economy” (910), the “price” (672) of crude oil, and the “market” (536). The repercussions are signalled by the “collapse” (411) of the “stock market” (478) and the “fear” (651) for what is looking like a “war” (294) owing to the “impacts” (423) and the “effects” (326) produced. In the Spanish tweets, the supranational dimension shows even greater strength in the “world pandemic spread” (cluster 5), which evidences that Covid-19 knows no boundaries.

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Tweet cl-5 (world pandemic spread): It’s official confirmed cases of coronavirus in Chile now. Covid Chile pandemic (score= 7514.0878). In this cluster, people are concerned about the “cases” (10,189) “confirmed” (3095), “new” (3054), or “suspected” (994), and about Covid-19 having “arrived” (1538) in “Argentina” (1525), “Colombia” (1342), “Peru” (1281), “Mexico” (930), “Venezuela” (926), “Chile” (864), “Ecuador” (755), “Panama” (602), “America” (453), “Brazil” (425), “Paraguay” (428), “Bolivia” (281), and in all “Latin America” (169). The inevitable consequences of this unstoppable advance of Covid-19 are the closure of markets and industries, which are measures that affect countries worldwide, including Spain. Nonetheless, in the clusters, the country “blocks” were differentiated into “countries forced confinement (cluster 8)” and “Spanish lockdown” (cluster 2). In “countries forced confinement” (cluster 8), the messages outline a dimension that concerns the “world” (1690), which not so metaphorically must “close” (828) the “door” (850). This reflection advanced following a sports event: the “football” (225) match of the “Champions League” (100) played by the “Atalanta” (29) and “Valencia” (150) teams at the San Siro stadium, in Milan, on February 19, 2020, which was attended by 36,000 people. After this event, all other events occurred behind closed doors or were suspended. Tweet cl-8 (countries forced confinement): Owing to the coronavirus outbreak, the UEFA confirms that the Champions League match between Valencia and Atalanta at Mestalla, and the Europa league match between Inter and Getafe at San Siro will be played behind closed doors (score= 1801.963). Now, in “Spanish lockdown” (cluster 2), the “government” (1813) of “Madrid” (2083) “suspends” (1764) all “activities” (763) in “March” (1209), signalling the onset of the “lockdown” (1058), which touches the “University” (622), “sport” (429), and the “school” (284). All is “cancelled” (195) “now” (659). Tweet cl-2 (Spanish lockdown): the Basque government will study each case to cancel events (score= 1247.5044). In summary, in the group of tweets in Spanish, we find contents concerning the containment measures of the contagion. We also find greater attention than what happens outside Spain, so the presence of interest in supranational levels is more marked than what emerged in the group of Italian tweets. This can be attributed both to the presence of larger

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extra-­national linguistic communities and to the possibility of having more time to prepare themselves for the arrival of the pandemic in the Spanish context. 4.3   Analysis of French Tweets In the French language, Twitter users symbolized the Covid-19 pandemic by seven dimensions. The three main dimensions, explaining 60% of inertia, are the impact (28% of inertia), the intervention level (18% of inertia), and the crisis (14% of inertia; Fig. 5.3). With the increasing spread of the Covid-19 pandemic, European countries were confronted with a greater risk of contagion, leading people to start to ponder about the consequences of the virus spread on the social fabric. The first factor distinguishes the productivity impact (positive pole) from the social one (negative pole); specifically, focusing attention on the consequences regarding loss in productivity and in the economic sector, and focusing on the perception of a threat to human life. The second factor distinguishes the interventions at the micro (negative pole) from those at the macro level (positive pole). French corpus presented 11% of neutral sentiment connected with the cluster of the Individual prevention strategies (see Table 5.5). When articulating clusters for French tweets, we observed a much more explicit alternation between local and supranational perspectives, to a point where they were equivalent in the representation of the Covid-19 pandemic. Notably, among the tweets belonging to “French contagion” (cluster 1), there is “coronavirusfrance” (2585), which is an expression that nationalizes the hashtag. Hence, we can argue that the distinction between local and supranational topics originates in Twitter users’ habits, signalling their conscious use of the platform and its spaces. In this cluster 1, the most meaningful words were related to nationals’ hashtags on Covid-19—“coronavirusfr” (801), “coronavirusenfrance” (556)—and the cluster was mostly dedicated to “France” (7741), to the “French” (745), and to “Emmanuel Macron” (332). Tweet cl-1 (French contagion): Emmanuel Macron brings together general reports on research at Élysée with the primary objective of taking stock of possible treatments and vaccines against the virus and programs undertaken to fight it (score= 812.378). Although we collected tweet data during the initial phase of the COVID-19 pandemic, the “world pandemic spread” (cluster 5) describes a reality made up of “cases” (10,730), “deaths” (2113), and “confirmed,”

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which crosses not only “regions” (338) but also “Senegal” (329), “Cameroon” (188), “Belgium” (361), “Egypt” (147), “Morocco” (243), “Africa” (304) and “Quebec” (157). Tweet cl-5 (world pandemic spread): Canada, Quebec new case of coronavirus infection in British Columbia which leads to an increase in the number of people infected in Canada (score= 8461.218). Similar to the results for the Spanish tweets, French tweets also draw the contours around the portions of the world where the French language is spoken and around nations that have already touched each other or are close, either historically or culturally. In French tweets, the Italian situation also appeared and had a cluster entirely dedicated to its events, “Italian lockdown” (cluster 3), which are represented by the words “quarantine” (1621), “Milan” (243), the “North” (282), its “ministers” (1292), the whole “country” (1195), and where everything has been “suspended” (281). Tweet cl-3 (Italian lockdown): the first outbreak of coronavirus in an Italian town, it has already produced some dead this Wednesday. To deal with the epidemic, the country has taken exceptional measures, deciding to close all schools and universities provisionally (score= 1234.0793). In the cluster dedicated to Italy, “Europe” (387) comes into play, and it reappears in the “French lockdown” (cluster 6). In cluster 6, the tweets are dedicated to national events owing to the “epidemic” (3950) which became a “pandemic” (738) when the “WHO” (593) decided upon it, producing “inexorable” (78) repercussions. These repercussions, in turn, were decided by “Macron” (1340) and pertained to the “closure” (740) of “schools” (1319) and “universities” (272). The flow of conversations also highlights a search for the “epicentre” (59) and for the “Chinese” (458), which are represented by “Wuhan” (326). Tweet cl-6 (French lockdown): the great confrontation about different opinions between Anne Hidalgo and Agnès Buzyn. Paris coronavirus there’s or is just a small epidemic in China. Agnès Buzyn lies because, as a past Minister of Health, she knows that covid is not a classic flu (score= 2078.124). Further, we extracted “individual prevention strategies” (cluster 8), which relates to tweets talking about a collection of tools useful for prevention and sanitation, such as the importance of “washing” (863), using “gels” (909), “hydroalcoholic” (432) solutions, and always having these “bottles” (90) with you, as well as to continue with social distancing.

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Tweet cl-8 (individual prevention strategies): because of the coronavirus COVID-19, we ask you not to shake hands or kiss to greet others (score= 3930.3231). On the national dimension, there are two clusters: “national elections risk” (cluster 2) and “national crisis” (cluster 4). Cluster 4 signals the emergence of a collective fear/feeling linked to the approaching COVID-19 pandemic, thus greatly resembling “people panic” (cluster 1) in Spanish tweets group, although our different labelling respects the specificity of the languages and how the same sentiment was expressed in Twitter. For example, among significant words, “psychosis” (271) was higher than “panic” (165), both of which are fears dictated by “illness” (247) and connected to COVID-19. Moreover, there are words about symptoms, including “coughing” (324), and the “media” (274) and “Twitter” (130). The presence of the media brings forth questionings about their role in spreading the news about and in presenting Covid-19, the contagion, and the pandemic. Tweet cl-4 (national crisis): from in people realize that the Chinese government maintains psychosis. Nonetheless, it is so serious that we have at least two years of COVID-19 disease ahead of us (score= 2078.124). To understand “national crisis” (cluster 4) it is necessary to remember the French events during the period. The “crisis” (2117) was linked to the “elections” (465) of March 15, 2020, which were held despite the bulletins recording 4499 infected and 91 deaths. The French people who were called to the polls felt at “risk” (671) and seemed to understand well that this was a “political” (554) “question” (483). Accordingly, the words “Abstention” (55) (around 53–56%) and the “RT” index (136) appeared. The RT index serves to rate a disease’s ability to spread by describing the average number of people that one infected person can pass the virus to. The tweets described a widespread concern about how the arrival of Covid-19 in the “municipal” (1690) city of Paris would be managed by the authorities. Tweet cl-4 (national crisis): Agnès Buzyn says it has developed preventative management of the coronavirus. If it is so we must expect the worst for the Paris municipalities (score= 2624.8805). Alongside this dimension of risk and crisis there are the “economic” (364) and “social” (261) ones. We deemed as being no coincidence that in both Spanish and French tweets we observed exclusive clusters for “economic impact” (cluster 7). As already reported for the Spanish tweets, the French tweets linked the economic crisis to “companies” (1144),

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“stock exchange” (627), “oil” (362), and evaluated that it would have an “impact” (477) “worldwide” (461). To address it, “protection” measures (375) were needed because they did not only concern “finance” (179), “banks” (184), or “euro” (111) but also those who worked in the “tourism” (152) and “show” businesses (161), as well as other “sectors” (125) that would stop. It was an “European” (115) crisis related to “white-­ collar” workers (79) and “workers” (28). Tweet cl-7 (economic impact): is it better to lose people or to bring down the world economy? Surprisingly, the point is that the old and the weak seem to be dying (score= 565,635). In the tweets of the French group, an attention emerges towards the methods of contagion and prevention that mainly concern a national level, as well as the theme of the crisis, and then there is the opening towards a supranational level as soon as one looks at the impact of the pandemic on the economic system. The economic system is certainly connected on a global level, and this trait emerges here with extreme clarity. 4.4   Analysis of German Tweets The German Twitter users symbolized the Covid-19 pandemic by seven dimensions, of which the first three and the last one are the most interesting: the impact (22% of inertia), the contagion (17% of inertia), the reaction (16% of inertia) (Fig.  5.4), and the sensitivity (9% of inertia)

PEOPLE_PANIC ITALIA_LOCKDOWN

PASSIVE

WORLD_PAN_SPREA

Y Axis

NAT_EVENT_CANCE

GERM_CONTAGION

0,5

CONTAGION

0,5

POLITICAL_DIMEN

0,0

0,0

Z Axis

SPORT_EVENT_CAN

SENSITIVITY 1,0

REACTION

ECONOMIC_IMPACT

-0,5 -0,5 -1,0 ACTIVE

X Axis

Fig. 5.4  Symbolic space emerging from the German corpus

0,5

IMPACT

0,0

-1, 0

SOCIAL

-0,5

SENSE

HEALTH

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(Table 5.5). The most relevant dimension setting communication is the infection spread impact both in terms of health and social interactions. The reaction is the last main dimension setting, the sense-making space (Fig. 5.4), distinguishing the active positioning of making choices from the passive positioning of accepting what have been decided. As in the Italian symbolic space, in the German language, there is a distinction between those who decide how to manage the pandemic and those who accept others’ decisions and follow directives. As in the Italian language, there is a difference between the rational reaction to contagion and the emotional one. The relevance of the last factor lies in the necessity to distinguish a reasonable emotional reaction leading to an effective coping behaviour, such as fear, and an exaggerated reaction not helping the protection, such as panic, that is, scared people tend to choose protective behaviours avoiding danger while panic, being overwhelming, tends to produce instinctive, unreasonable behaviours and not necessarily protective ones. The relevance of the last factor highlights a difference between the German and the Italian culture: the first values the emotional control, considering its intense emotional expression ridiculous, while the latter values the emotional expression, appreciating its ability to call for a specific interactive response. The last factor (sensitivity) is relevant since it distinguishes two clusters, which are located in the same position in the factorial space, people panic (Cluster 4) and the economic impact (Cluster 7) (Table 5.6). As we better explain in the following paragraphs, the first is located on the negative pole (exaggerate sensitivity) and is associated to a negative sentiment of anxiety and panic for the viral spread, while the second one is located on the positive pole (reasonable sensitivity) and is associated to a positive sentiment of pride for being able to cope with the health challenge. This pragmatic approach to emotional arousal matches with the low rate of negative sentiment (61%) compared to other corpora. It is related to the government’s reaction (14%), people panic (13%), the global infection spread (13%), the health impact (11%), and the sport events cancellation (10%), all topics associated to negative feelings or information. The pragmatic approach seems to influence the neutral sentiment rate too (28%). It is related to decisions aiming to reduce the contagion, such as the Italian lockdown and the social event cancellation, both considered as a logical consequence to the viral spread. But most interestingly, we also found a positive feeling of pride in German messages related with the

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ability to cope with the health crisis, managing policymaking, and finding solutions to face challenges. The government’s reaction to the viral spread is associated with a sentiment of distrust in the political and scientific institution emerging from the messages. The prime minister Angela “Merkel” (1987), her party “CDU” (553), the Minister of Health, “Jens” Spahn (299), and the Robert Koch institute, “RKI” (1075), are the key referents for information, although their statement and comments do not seem to reassure citizens, who express their discontent online. Tweet cl-1 (Government reaction): Federal governor Jens Spahn constantly repeat that Germany is prepared to face coronavirus but the longer I look at it, the more I am well prepared, the more I get the feeling that Germany is once again prepared for nothing at all (score= 26,412.5). The increasing number of “cases” (697), “infections” (454) and “dead” (1005) aroused feelings of distress since the “pandemic” (843) had reached “Germany” (7252; “Federation” 751). Increasing feelings of “anxiety” (1235) and “panic” (1178) arose in the population (“human” 2493; “people” 1130), feelings that have to be seriously considered since they are justified by the events. Daily life activities are threatened such as “walking” (2753) and “correct” (312) prevention tools “should” (464) be used such as “disinfectants” (729) to take “care” (309) of oneself. Tweet cl-4 (People panic): the best protection against paranoia and panic take fear seriously fear space give fear look in the eye and above all do not make fear ridiculous, even unfounded fear, panic coronavirus covid (score= 15,931.8). All around Europe the infection is spreading (Cluster 5), leading to the closure of the incoming voyager from infected countries and starting the infection spread monitoring of infected “case” (1350) all around the “world” (305). Tweet cl-5 (Global infection spread): coronavirus today Sunday are cured and worldwide still ill suspect criteria fever and travel two weeks ago to china south Korea Singapore Italy Iran all other feverish or coughing people have no covid (score= 6454.2). While cluster 5 focuses on foreign countries such as “China” (1702), “United States” (858), “Iran” (312), and more generally, “Europe” (604), showing an increase in the “positive” (1061) “test” (1303). The messages in cluster 6 focus on the domestic spread. Tweet cl-6 (Health impact): number of coronavirus cases in Berlin rises news politics economy berlinersonntagsblatt germany health

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coronavirusgermany coronavirus germany coronavirus update covid covid covid corona covid (score= 26,848.6). This is the cluster of the German contagion (“coronavirus Germany” 3263; “coronavirusde” 2429; “corona Germany” 1339; “coronavirusgermany” 981; “Germany” 1331) and it focuses mostly on the decisions of the “political” (910) and scientific institutions, such as the “Health Minister” (183) and the Robert Koch Institute (“RKI” 329). This cluster differs from the previous one due to the restriction to a specific geographical area and the relevance of the political and health institutions. While the social event cancellation (Cluster 8) is associated with a neutral sentiment and involves educational and cultural events of the main cities, such as “Berlin” (948), “Hanover” (261), “Munich” (231), “Frankfurt” (219), and “Stuttgart” (141), the sport events cancellation (Cluster 2) is associated with a negative feeling of loss. Although this last is the smallest cluster, it seems to be supported by passionate “soccer” (858) or “Bundesliga” (1249) “fans” (577) and “spectators” (764). Tweet cl-8 (Social event cancellation): Austria coronavirus new measures for live events until the beginning of April cancellation of outdoor events via participants cancellation of all in door events via participants Austria Oesterreich events news (score= 28,129.5). Tweet cl-2 (Sport events cancellation): the derby Borussia vs fckoeln will now be the first ghost game in the history of the Bundesliga dfb dfl official as much as my heart hurts as a football and effzeh fan, it is still right and necessary coronavirus bmgkoe (score=12,942.1). Also, the Italian lockdown (Cluster 3) is associated with a neutral sentiment since it is considered a rational and inevitable “measure” (1627) taken by the “government” (905) to contain the infection “spread” (862). As we previously highlighted in the factorial space interpretation, two main symbolic dimensions setting the communication are the distinction between sense and sensitivity (Factor 2) and the value of the emotional control (Factor 7). This could explain the sentiment neutrality in considering the national “quarantine” (1642) in “Italy” (4502). The “closure” (1606) (“shut down” 1765) of educational and social activities (i.e., “schools” 2734) is a forced choice and, additionally, is abroad. Tweet cl-3 (Italian lockdown): Italy closes all schools and universities Italy wants to restrict large parts of public life in the fight against the coronavirus epidemic from Thursday on all schools and universities will remain closed until March (score= 31,609.8). In the German corpus, there is also a positive sentiment connected to the cluster 7, the economic impact. As we previously highlighted, it seems

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to be associated with a sentiment of pride for being able to professionally face the Covid-19 challenge although the messages are about the pandemic impact on the productivity system. The messages focus mostly on the labour market (“work” 324; “employer” 160; “companies” 464) and more in general on all the productive sectors that are affected by the health “crisis” (530), focusing particularly on the measures that have been taken to overcome the issues. Tweet cl-7 (Economic impact): coronavirus & labour law the most important questions employers can apply for short-time work benefits due to corona how employers should proceed to answer and the other questions covid thread (score= 6147.9).

5  Conclusions The analysis of the tweets and the discussion of the results in the previous paragraphs allow us to understand how Spain, France, and Germany (represented here by the tweets in their respective languages) are preparing for the arrival of the virus after Italy was hit by it; how the actions of governments are perceived by citizens and commented on Twitter. It also allows us to collect the fears connected to the global dimension of risk and to the crisis—especially economic—that the pandemic will inevitably produce. The tweets tell us about a clear perception of the economic impact of the pandemic that emerges in the Spanish, French, and German groups and is pulled out of the Italian cluster on the lockdown. For the reconstruction of the representation of the pandemic and the containment measures adopted in individual countries, the ETM proves to be an extremely useful method. In fact, it allows us to understand how the different perceptions of the crisis produced by the pandemic undergo variations depending on the proximity or distance from the risk of contagion. The more the virus is perceived by people as close, the more containment measures increase, the more real the danger and consequences of an economic-­ social as well as health crisis become. Italy suddenly found itself catapulted into the health crisis produced by the Covid-19, the reactions in the group of tweets in Italian are all negative for these reasons. Italians tell in their tweets about an invisible enemy, of which not even science knows anything. They are therefore activated to search for information, and consequently the search for information collapses into the communicative practice of gatewatching [RQ2]. It is a question of activating—for contingent needs—the sharing of information

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and the communication of feelings, opinions, and fears is grafted onto them [RQ1]. The supranational dimension is more present in the group of tweets in Spanish. They tell us about the preventive measures put in place by the Government, but above all, they keep track of how those who know that the virus will also reach its territories begin to prepare [RQ1 and RQ2]. What is most striking and is told in the tweets—starting with the Spanish group up to the German one—is the waiting for the different lockdowns and therefore for the actions of governments to stem the spread of the virus. The variability of the restrictions accompanies the level of perception of fear and marks the sentiment. In fact, in the Spanish tweets, we find a neutral sentiment, which allows us to understand that high levels of negative sentiment are the consequence of the adoption of rigid containment measures [RQ1]. An alternation between national and supra-national level is more present in the tweets of the French group which therefore tell us of an attention in the dissemination and collection of information that looks both at the French and the international context. Furthermore, attention to the indications coming from the European bodies emerges. The idea of a pandemic that cannot be stopped by a single state is gaining ground; these considerations are accompanied by a negative sentiment [RQ1 and RQ2]. The tweets in German tell us about a polarization between those who decide which actions and measures to apply to contain the pandemic and those who face the dynamics linked to the everyday life of the crisis. It is possible to distinguish—in this group of tweets—a practice of discerning

Fig. 5.5  The gatewatching of emergencies. Source: Reworking starting Bruns’s scheme (Bruns, 2008)

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the most useful emotions in facing the pandemic event, with a clear distinction between fear and panic [RQ1 and RQ2]. The analyses produced here show that in the first period of the pandemic that activated on Twitter by users was a practice of searching for information, which generates an emergency gatewatching, which in turn is characterized by the introduction into the tweets of a multitude of feelings and opinions that could not find an outlet in another place due to the physical distancing between individuals caused by lockdowns (Fig. 5.5). Emergency gatewatching is a specific gatewatching practice because it combines the identification and sharing of important information material as soon as it becomes available, with the communication of emotions, opinions, and sentiments. Thus, it is not only a practice of participation in the publication of news and monitoring of them, but it merges within this practice that of sharing feelings, indispensable for those who face an enemy.

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Lebart, L., & Salem, A. (1994). Statistique textuelle. Dunod. Lovari, A. (2020). Spreading (dis)trust. Covid-19 misinformation and government intervention in Italy. Media and Communication, 8(2), 458–461. https://doi.org/10.17645/mac.v8i2.3219 Manguri, K. H., Ramadhan, R. N., & Amin, P. R. M. (2020). Twitter sentiment analysis on worldwide COVID-19 outbreaks. Kurdistan Journal of Applied Research, 54–65. https://doi.org/10.24017/covid.8 Marcos, J. (2020, March 28). Paralizada toda actividad no esencial en España. El País. https://elpais.com/espana/2020-­03-­28/el-­gobierno-­amplia-­el-­confinamiento-­ lostrabajadores-de-­actividades-­no-­esenciales-­deberan-­quedarse-­en-­casa.html PAHO. (2020). Understanding the infodemic and misinformation in the fight against Covid-19. Pan American Health Organization, World Health Organization. Factsheet N.5. Preso da: https://iris.paho.org/bitstream/handle/10665.2/52052/Factsheet-­infodemic_eng.pdf Petersen, K., & Gerken, J. M. (2021). #Covid-19: An exploratory investigation of hashtag usage on Twitter. Health Policy, 125, 541–547. https://doi. org/10.1016/j.healthpol.2021.01.001 Raghav, R. H., Vemprala, N., Akello, P., & Valecha, R. (2020). Retweets of officials’ alarming vs reassuring messages during the COVID-19 pandemic: Implications for crisis management. International Journal of Information Management, 55, 102187. https://doi.org/10.1016/j.ijinfomgt.2020.102187 Rambukkana, N. (Ed.). (2015). Hashtag publics. The power and politics of discursive networks. Peter Lang. RFI. (8 march, 2020). Coronavirus: Berlin appelle à annuler les grands rassemblements. https://www.rfi.fr/fr/europe/20200308-­c oronavirus-­b erlin-appelleannuler-­grands-­rassemblements Savaresi, S. M., & Boley, D. L. (2004). A comparative analysis on the bisecting K-means and the PDDP clustering algorithms. Intelligent Data Analysis, 8(4), 345–362. https://doi.org/10.3233/ida-­2004-­8403 Steinbach, M., Karypis, G., & Kumar, V. (2000). A comparison of document clustering techniques. In 400th KDD workshop on text mining (pp.  525–526). Boston. http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.125.9225 Vygotskij, L. S. (2010). Lo sviluppo psichico del bambino. Editori Riuniti. Weller, K., Bruns, A., Burgess, J., Mahrt, M., & Puschmann, C. (Eds.). (2014). Twitter and society. Peter Lang.

CHAPTER 6

The Covid-19 Pandemic in Canadian Newspapers: An Analysis of the Journalistic Articles as Risk and Crisis Messages Olivier Champagne-Poirier, Marie-Eve Carignan, Marc D. David, Tracey O’Sullivan, and Guillaume Marcotte

1   Introduction On January 27, 2020, a first case of Covid-19 was confirmed in Canada when a Toronto resident returning from China tested positive for the SARS-CoV-2 coronavirus. Less than two months later, positive cases of Covid-19 were reported in every province and territory across the country (Arsenault, 2020; Blanchette Pelletier, 2020; Giles, 2020). The first major government measures to curb the spread of the virus were introduced in March 2020, with the Canadian federal and provincial governments closing the land border with the United States (except for essential goods),

O. Champagne-Poirier • M.-E. Carignan (*) • M. D. David Department of Communication, Université de Sherbrooke, Quebec, Canada e-mail: [email protected]; Marie-Eve.Carignan@ USherbrooke.ca; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. La Rocca et al. (eds.), Infodemic Disorder, https://doi.org/10.1007/978-3-031-13698-6_6

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repatriating their nationals, announcing containment measures, closing schools, and suspending the operations of a large number of businesses and companies. In less than a year, Covid-19 has gained a very prominent place in the media and scientific spheres. Researchers Mireille Lalancette and Michel Lamy (2020) describe media coverage of the pandemic as a “media eclipse,” in that pandemic-related news and topics take up nearly the entire media landscape. Unsurprisingly, in the face of such an unusual phenomenon (in terms of magnitude), a whole scientific literature has rapidly developed on the topic. Numerous researchers have investigated the impacts of the pandemic from both a communication and an information standpoint (Bridgman et  al., 2020; Higgins et  al., 2020; Lacroix & Carignan, 2020; Tejedor et  al., 2020; Villena-Alarcón & Caballero-­ Galeote, 2020).

2  Crisis and Risk Communication This chapter focuses on media coverage of the first three months of the Covid-19 pandemic in Canada. Here, as we focus on the early stages of the pandemic, the concept of “crisis communication” looms large. Indeed, described as a health, social, and economic crisis, Covid-19 swiftly plunged the world into a state of crisis: “crises most often create such a severe disruption of order and sense of normal life that people cannot predict what will happen” (Seeger & Sellnow, 2013, p.  63). Media coverage of the pandemic contributes to crisis communication by attempting to make sense of the new coronavirus and its many impacts on global order. Several theoretical models have been put forward to understand crisis communication, based on deconstructions of the pandemic into different phases or steps. These include the “Situational Crisis Communication

T. O’Sullivan Interdisciplinary School of Health Sciences, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada e-mail: [email protected] G. Marcotte Research Professional at the Université de Sherbrooke, Québec, Canada e-mail: [email protected]

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Theory” (SCCT) developed by Timothy Coombs and the “Crisis and Emergency Risk Communication” (CERC) model of the Centers for Disease Control and Prevention (CDC). The SCCT model distinguishes between three communication phases during a crisis, expressed in the nomenclature of pre-crisis, crisis, and post-crisis (Coombs, 2012). The CERC model, designed following the events of September 11, goes a step further by splitting a crisis into five phases: pre-crisis, initial event, maintenance, resolution, and evaluation. The works of these authors, which can be said to advocate a developmental approach to crisis communication, highlight the relevance of focusing on crisis communication from a temporal standpoint. The basis of this approach is that the information and communicative environment of a crisis changes over time. As the crisis unfolds, the initial uncertainty is reduced as information becomes available and new issues arise. As the crisis develops, therefore, different kinds of communication processes and different kinds of information are needed. (Sellnow & Seeger, 2021, pp. 66–67)

Our interest in the media coverage during the first three months of the pandemic in Canada stems from a desire to better appraise what the above authors call the “pre-crisis” and “onset of crisis” (Coombs, 2012) or the “pre-crisis,” “initial phase” and “maintenance” of the pandemic (CDC, n.d.). A few years before the outbreak of the SARS-CoV-2 virus, Madhav et al. (2017) noted that the risks of a global pandemic were on the rise, as a result of globalization, greater travel, urbanization, changes in resource use, and more intensive environmental exploitation (Madhav et al., 2017). Indeed, “[c]rises occur when risks are manifested” (Seeger & Sellnow, 2013, p. 239). Our research interest also connects with the concept of risk communication. Even before the World Health Organization (WHO) declared a global pandemic (March 11, 2020), and the Canadian government introduced drastic measures to respond to the crisis that had arrived on its doorstep (i.e., during the “pre-crisis”), communication mechanisms were already in place to communicate the risks associated with the new virus. Hence, our interest in the media coverage focuses on a start date of January 27, 2020. Beyond the temporal nuances between the two concepts, many researchers believe that “crisis communication” and “risk

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communication” are intertwined, such that they should be considered at the same time. Some have sought to model risk communication in times of crisis and to situate various related considerations. For example, according to the IDEA model for effective instructional risk and crisis messages (Sellnow & Sellnow, 2014), risk communication in times of crisis can be best assessed via four components: (1) Internalization (are the individuals who are affected by the risk able to understand the risks that concern them?); (2) Distribution (are risk messages delivered via effective communication channels?); (3) Explanation (is the risk information appropriate, and formulated clearly and consistently?); and (4) Action (do the messages provide a clear process for individuals to take action and protect themselves from the risk?). In sum: the IDEA model provides a framework for designing effective messages when the goal is to instruct non-scientific publics to take appropriate actions for self protection during risk and crisis events. (Sellnow-Richmond et al., 2018, p. 140).

Other researchers have investigated the role of communication in the decision-making processes of individuals confronted with risk. This is the case of Dunwoody and Griffin (2015), who developed the “Risk Information Seeking and Processing” model. In their view, the information provided to individuals in times of crisis is very important. However, the impact of this information must be nuanced by four factors that shape the assimilation of information: (1) individual characteristics; (2) motivational variables; (3) beliefs about the risk in question; and (4) perceived ability to obtain information about the crisis. According to this model, an individual’s ability and willingness to assimilate the information presented to them in times of crisis may depend, for example, on socio-demographic traits such as level of education; the mechanisms in place that may encourage or prevent their assimilation of new information; personal perceptions of the crisis and the risk it poses to them; and the amount of information they need to make up their mind about the crisis and the risks it represents. The theoretical research presented above suggests that crisis and risk communication, particularly in the context of the Covid-19 pandemic, is deserving of analysis. This analysis should focus particularly on the dimensions of the temporality of key moments in the crisis; the nature of the public health messages issued to the population; the nature of the communication mechanisms; and the intensity of the communication

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initiatives implemented by governments, experts, or public health agencies. It also appears important to understand the impact of this communication as being intrinsically bound with the particularities of the individuals to which it is addressed. Moreover, the question of media coverage is inherent in crisis and risk communication. In the words of Sellnow and Seeger (2021), this is because of the intense media scrutiny that follows a crisis. […] Moreover, the media often seek immediate explanations regarding cause and blame and disseminate this information very broadly. The harm created by a crisis, including victims’ stories, is often dramatically represented in the press. During a crisis, this pressure for immediate explanations about cause and consequences, and the very broad public dissemination of those messages, further compresses time and intensifies the consequences of decisions and public statements made by organizations. (pp. 68–69)

Thus, to fully understand the role of the media in communicating a crisis, and existing or evolving risks, three questions must be asked: Who are the actors featured by the media? What aspects of the crisis are the media covering? And how is the media coverage evolving over time?

3   “Crisis and Media” or “Media in Crisis”? The institutional and societal contexts in which media coverage of crises and risks unfolds must be taken into account to fully grasp the constraints to which news professionals are subjected. Journalists have a vital role to play in society by making information tangible, accessible, and intelligible to the public (Hanitzsch & Vos, 2018). This “transmission” role is all the more important in times of crisis. Anthony and Sellnow (2011), who studied the journalistic coverage of Hurricane Katrina in 2005, found that during a crisis, local media are essential for delivering real-time information to the public—which, in turn, helps citizens better understand the crisis. David and Carignan (2017) made the same observation when examining the railway explosion that took place in the Quebec town of Lac-­ Mégantic. More recently, the same observation was highlighted in the research of Olsen et al. (2020), who also point to the crucial role of the media in the context of the Covid-19 crisis.

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Several studies showed how citizens turned to traditional media as soon as the health crisis became apparent, and their media consumption spiked significantly during the pandemic, for example, in Belgium (Hanseeuw et al., 2020) and in the United States (Casero-Ripolles, 2020). Hence, a number of researchers have looked at how journalistic news has been produced during the COVID-19 pandemic. Ogbodo et  al. (2020) studied the framing used by journalists around the world during the crisis. They concluded that while the media coverage is substantial, the framing lacks coherence and effectiveness. This can be explained by the media’s obsession with breaking news (Ogbodo et  al., 2020). Tejedor et  al. (2020) studied the journalistic coverage in Spain and Italy during the first months of the pandemic, and uncovered, among other things, a preponderance of news journalism, a willingness to humanize the crisis through an emotional representation of the pandemic, and the ubiquity of international news (Tejedor et al., 2020). The pandemic placed multiple pressures on the media: financial pressure due to waning advertising revenues (Winseck, 2018; Radcliffe, 2020) and a declining economy (Olsen et al., 2020), time pressure due to the frantic pace of news (Monnier, 2020), as well as pressure resulting from the shortage of staff caused by the economic downturn. For example, in the early months of the pandemic, some 100 Canadian media outlets had to downsize and approximately 50 had to temporarily or permanently shut down (Lacroix & Carignan, 2020), while in the USA, 36,000 journalists lost their jobs (Radcliffe, 2020). Journalists working within this media ecosystem have seen a shift in their practices (Nielsen, 2018). The precarious economic situation of the media, the declining world economy, the frantic pace of news and new media practices (working remotely and/or having a declining presence in the field, etc.) are all factors that shape the work of journalists in times of crisis. Yet, as we have seen, the media play a key role in communicating crisis and risk, namely, by passing on verified information to the public, questioning the decisions of crisis managers, and echoing the public’s questions. As such, journalistic coverage ends up creating systems of representation that explain, among other things, who is being affected by a crisis, what the most worrying aspects of the crisis are, and how the crisis situation is developing. To shed greater light on crisis and risk communication during the early stages of the Covid-19 pandemic in Canada, this chapter sets out to answer

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the question, “What defined the Covid-19 media coverage within the first three months of the virus arriving in Canada?”

4  Analytical Framework This research builds on pre-existing empirical knowledge. The results presented in this chapter were obtained using an analytical grid developed inductively during a prior study. To arrive at the results presented in the remainder of this text, we used this grid as our analytical framework. In what follows, we explain its origin and components. In the course of previous research, we conducted a qualitative analysis of initial Canadian journalistic coverage of the Covid-19 pandemic. More specifically, we analyzed articles published by 20 Canadian daily newspapers1 between January 27 and April 27, 2020, to theoretical saturation. These dates cover the three months following the outbreak of the Covid-19 pandemic in Canada.2 In all, 512 articles were coded, following a three-­ level coding process (open, axial, and selective) commonly used in qualitative and inductive approaches (Corbin & Strauss, 2015; Labelle et  al., 2012; Lejeune, 2014). The articles were randomly selected from among the 40,436 articles published by these 20 daily newspapers during this period.3 Rather than being derived from quantitative criteria, the number 512 refers to the threshold of “theoretical saturation,” that is, the point where new data was no longer informing the categories discovered and where we judged that the categories uncovered satisfactorily reflected the complexity of the phenomenon under study (Corbin & Strauss, 2015). This process allowed us to better understand the characteristics of the initial journalistic coverage of the Covid-19 pandemic in Canada. We consider that this coverage is expressed through a simultaneous tripartite process of staging the protagonists (Who?), selecting different facets of social reality (What?), and positioning with respect to professional ideals (How?). 1  The 20 dailies were: Vancouver Sun, The Province, Toronto Star, Toronto Sun, Winnipeg Sun, Winnipeg Free Press, Calgary Herald, Edmonton Journal, The Star-Phoenix, The Leader Post, The Telegraph Journal, The Chronicle Herald, The Globe and Mail, National Post, Journal de Montréal, La Presse +, Acadie Nouvelle, Cape Breton Post, The Telegram, and The Guardian. 2  The first official case of Covid-19 in Canada has been linked to January 27, 2020. 3  Explanations regarding our sample’s composition are provided in the methodology section of the article, under 4.1 Scope of the sample.

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4.1  Who? Few individuals or groups can claim to have been unaffected by the pandemic. Yet not all individuals or groups are portrayed as being affected by Covid-19 in newspaper articles. Our analyses have indicated that journalistic coverage of the pandemic paints a picture in which certain protagonists or groups are especially affected or concerned. More specifically, the protagonists or groups identified in the analysis of the 512 articles were placed into 19 categories (see Table 6.1).

Table 6.1  List of the 19 protagonists or groups identified in the analyzed articles   1. Elected federal politicians mentioned in the article [other than Minister of Health] (i.e., Prime Minister [Justin Trudeau], Minister or Member of Parliament)   2. Elected federal politicians mentioned in the article [other than Minister of Health] (i.e., Prime Minister, Minister or Member of Parliament)   3. Elected municipal politicians (i.e., mayor or city councilor)   4. President of the United States [Donald Trump]   5. Public health department (regional, provincial, or federal)   6. Minister of Health (provincial or federal)   7. Individuals physically affected by COVID-19 (cases or deceased persons)   8. Individuals socially affected by COVID-19 (i.e., people under quarantine or who lost their jobs, or high school or university students at home)   9. Physical health experts [aside from official public health actors] (i.e., physician, epidemiologist, pharmacist, or nurse) 10. Social science experts (i.e., political scientist, economist, psychologist, or communicologist) 11. Frontline or essential workers (i.e., doctor, nurse, social worker, specialized educator, teacher, or grocer) 12. Populations at high-risk (i.e., older adults, diabetic, person with cancer or respiratory disease) 13. World Health Organization and its leaders [Tedros Adhanom Ghebreyesus, Soumya Swaminathan, and/or Jane Ellison] 14. Economic or entrepreneurial actors (i.e., business leader, investor, or shareholder) 15. Cultural personalities (i.e., singer, actor, artist agent, or museum executive director) 16. Sport stakeholders (i.e., athlete, sport association, or league) 17. News or social media (print newspapers, television, radio, or digital media) 18. Groups or movements affiliated with conspiracy theories, the extreme right, or the promotion of civil disobedience (i.e., an anti-mask movement, or a movement advancing individual rights and freedom or anti-establishment behavior) 19. Law enforcement (police or army)

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4.2  What? The pandemic is an extremely complex phenomenon with many different facets; indeed, few aspects of daily life have not been upended by the coronavirus crisis. The initial coverage of the phenomenon in Canada addressed multiple themes. Our inductive analyses allowed us to categorize the issues covered in the 512 initially analyzed articles into 25 major themes (see Table 6.2). Table 6.2  The 25 major themes addressed in the articles   1. The evolution of the virus in the population and in laboratories (number of tests, number of hospitalizations, rise in the number of cases, the race for the vaccine, evolution of cases, etc.)   2. COVID-19 and its impact on mental health and loneliness   3. Drugs, alcohol, prostitution, and other addictions during the pandemic   4. COVID-19 and its impact on physical health (pneumonia, mortality, headaches, etc.)   5. Equipment for treating or preventing the virus (masks, ventilators, disinfectants)   6. Long-term care hospital centers (CHSLDs) or seniors’ residences   7. The interruption in the sports world (National Hockey League [NHL]), Olympic Games, etc.)   8. Difficulties facing the arts and entertainment (theatre, cinema, comedy festival, music festival, etc.)   9. Borders, travel, and travelers (flights, border closures, repatriations, etc.) 10. Shutdown of religious gatherings or places of worship 11. Economic slowdown (business closures, loss of jobs, contracts, etc.) 12. Canadian government financial assistance for citizens (Canada Emergency Response Benefit (CERB), Canada Emergency Student Benefit (CESB), assistance to small and medium-sized enterprises [SMEs], etc.) 13. Shortage of toilet paper, food products, and/or household items 14. Fundraising and public charities 15. The American election campaign 16. Diplomatic and political tensions between different countries 17. The role of the World Health Organization (WHO) in managing the pandemic 18. Environmental management of the pandemic: citizens’ pressure in favor of a “green” vision 19. Citizen protests and movements against COVID-19 measures 20. Application and reinforcement of preventive measures (lockdown, two-meter distancing, masks, etc.) 21. False news and belief in conspiracy theories 22. Restrictions on school activities; distance learning 23. Difficulties and closures in the restaurant and bar industry 24. Hate speech and incidents of hatred against an ethnic or religious minority 25. Killing in Portapique, Nova Scotia, during the pandemic (April 19, 2020)

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4.3  How? Our qualitative analysis of the initial journalistic coverage of the pandemic brought us to the same observation made previously by researchers investigating press discourse: “factual information—which is central to the mandate of the North American press, where it is recommended to separate facts from commentary—is increasingly mixed with opinions, judgments of all kinds, feelings and other markers of subjectivity” (Watine, 2006, p. 72, translated freely). Concretely, the inductive process during which the 512 articles were analyzed in depth determined that the initial journalistic coverage of Covid-19 contained eight journalistic intentions other than to inform (see Table 6.3). Finally, the team that carried out this previous research noted that a move away from neutral news coverage can sometimes be attributed to journalists adopting subjective discursive strategies. Seven strategies were identified as being specifically related to media coverage of the pandemic (see Table 6.4).

5  Methodology The findings of our previous qualitative study were applied to create an analytical grid allowing us to measure the prominence of the various characteristics identified in Canadian journalistic coverage. Naturally, our new objective required a shift in our ontological and epistemological stance. For the purposes of this quantitative and hypothetico-deductive Table 6.3 Journalistic intentions inherent in coverage of the pandemic

1. To inform *intention viewed as the standard of practice 2. To reassure 3. To raise awareness (especially by appealing or advising) 4. To denounce or criticize 5. To present testimony 6. To downplay 7. To speculate 8. To instill fear or dread 9. To sensationalize

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Table 6.4  Discursive strategies used to cover the pandemic 1. Self-staging in journalism (the journalist, being personally affected by the global pandemic, includes him- or herself in the news item, namely, by using “I”) 2. Speaking directly to readers (the journalist, knowing that their readership is directly affected by the pandemic, starts up a conversation with readers, namely, by using the “you”) 3. Use of personification (to deliver a more powerful message, the journalist lends human qualities to the virus or pandemic: the virus is a monster, a mass killer, etc.) 4. Use of a metaphor or analogy (the journalist links the virus, the pandemic, health measures or frontline staff to the collective imagination using a metaphor or analogy: the pandemic is a war, medical staff are guardian angels, etc.) 5. Use of comparison (to reframe the current pandemic, the journalist compares it with other viruses, crises, or events: comparing COVID-19 to the seasonal flu, Ebola, H1N1 flu, etc.; comparing the number of COVID-19 deaths to those associated with malnutrition around the world, AIDS, air pollution, etc.) 6. Use of direct quotations (the journalist supports their statements by quoting the protagonists) 7. Use of indirect quotations (the journalist supports their statements by paraphrasing the protagonists)

undertaking, we moved from a relativist and constructivist stance to a realist and post-positivist one (King & Horrocks, 2010). Concretely, we produced an analytical grid in SPSS. This is a grid that must be applied manually by analysts, who must read an article before filling out the grid. In brief, the grid is used to check whether the 19 protagonists or groups previously identified (see Table  6.1) are present or absent from the journalistic articles that make up the Canadian coverage of the pandemic. Next, the grid contains a variable asking the analyst to determine which of the 25 identified themes constitutes the main theme of a given article (see Table 6.2). Similarly, for another variable, the analyst must determine which of the main journalistic intentions (among the nine presented in Table 6.3) is present in the article. Finally, the grid contains a variable for which the analyst must determine whether the article contains discursive strategies (see Table 6.4).

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The grid also contains general variables regarding the article publication date,4 the author,5 and the newspaper concerned. The grid was used by 11 research assistants6 who were familiar with the coding process on SPSS and who underwent three hours of training on how to use the grid. Considering that the same research assistants had carried out the qualitative analysis of the articles (in the prior stage of the research), they were very familiar with the grid components. However, for more complex variables (in terms of coding) such as those requiring the main theme of an article to be determined (since an article may address more than one theme) or requiring the main journalistic intention to be determined (since an article may reflect more than one intention), a specific guideline was given. If an article addressed more than one theme or reflected more than one intention, the assistants were to count the number of lines. The theme or intention with the most lines was considered the main one. In the event of an equal number of lines, the theme or intention presented first in the article was considered the main one. 5.1  Corpus In addition to the qualitative approach used to formulate our analytical framework, we also focused our efforts on the initial media coverage of the pandemic, that is, articles published between January 27 and April 27, 2020. To do so, we consulted the Eureka and ProQuest databases and collected all articles published by 20 Canadian daily newspapers during the three-month period, using the keywords “covid” and “coronavirus.” Thus, all articles containing at least one of these two keywords were included in the corpus. This made it possible to identify a total population composed, as mentioned earlier, of 40,436 journalistic articles (see Table 6.5). Our number and choice of daily newspapers were based on three criteria. 4  The articles were divided according to their week of publication. The study period spanned 13 weeks. 5  This variable asks whether the article was written by a news journalist, an editorial writer (e.g., a columnist), a news agency, or an individual other than a news professional (letter of opinion from an expert, letter to the editor, etc.). 6  Many thanks to Zobaida Al-Baldawi, Vanessa Bournival, Gabrielle Crevier, Lina-Jeanne Grimard-Marchand, Alexandra Joseph, Emilie Leblanc, Ève Leclair, Guillaume Marcotte, Tania Mohsen, Roselyne Phaneuf, and Bianca Raymond for their contribution to this project.

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Table 6.5  Scope of the sample

1 2 3 4 5 6 7 8

Provinces

Dailies

British Columbia

Vancouver Sun The Province Journal de Montréal La Presse Toronto Star Toronto Sun Winnipeg Sun Winnipeg Free Press Calgary Herald Edmonton Journal The Star-Phoenix The Leader Post The Telegraph Journal Acadie Nouvelle The Chronicle Herald Cape Breton Post The Telegram

Quebec City

Ontario Saskatchewan

9 Alberta 10 11 Manitoba 12 13 New Brunswick 14 15 Nova Scotia 16

17 Newfoundland and Labrador 18 Prince Edward Island The Guardian 19 National media The Globe and Mail 20 National Post Total

Total number of articles published

1/8 random sample used for this study

2031 1721 2798

255 215 350

3397 2312 2667 1983 1159

425 289 333 248 145

2269 1861

284 232

1573

196

1691 1554

211 194

1349 1358

169 170

1462

182

1320

165

1342 2879

168 360

3710 40,436

464 5055

1. First, the articles from these newspapers had to be available on ProQuest or Eureka. 2. Second, our goal was to have an overview of the provinces and territories by integrating two daily newspapers per province or territory. For Newfoundland and Labrador and Prince Edward Island, only one daily newspaper was available per province. This is due to the fact that some daily newspapers in these two less populous provinces ceased

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operations as a result of the pandemic. Moreover, several smaller dailies were not available through the search engines used. Also, while they run bi-weekly newspapers, the three Canadian territories (Northwest Territories, Yukon, and Nunavik) have no daily newspapers available on ProQuest or Eureka. To compensate for this lack of data for some provinces and territories, we integrated two national daily newspapers distributed across Canada (see Table 6.5 for the list of daily newspapers). 3. Finally, among the dailies available on Proquest or Eureka for each province, we selected the two with the highest circulation. Given the resources available to us for this research project, we were unable to analyze all of the articles. Through pre-testing, we found that a research assistant could use our grid to code an average of 13 items per hour. Considering that the budget associated with the grant obtained for this project7 allowed for the equivalent of 400 hours of coding by assistants, we put together a corpus using a 1/8 random sampling strategy. In concrete terms, this means that one-eighth of the articles published by each newspaper were analyzed. Thus, the sample size of items used for the analyses presented in this paper is 5055 (see Table  6.5). Although our approach does not take into account all articles, we believe that our sample provides a complete and representative picture of the initial Canadian media coverage of the pandemic. 5.2  Analysis Given that it contains qualitative variables requiring reflection on the part of the analyst, our analytical grid has advantages and disadvantages. The variables concerning the main theme and the main journalistic intention 7  This project falls under a broader research project funded by the Canadian Institutes of Health Research. The overarching research project is entitled “The role of communication strategies and media discourse in shaping psychological and behavioral response to the COVID-19 outbreak.” The project involves an international community of researchers: Mélissa Généreux, Marc D.  David, Marie-Ève Carignan, Gabriel Blouin-Genest, Olivier Champagne-Poirier, Tracey O’Sullivan, Philip Schluter, Chi Shing Wong, Catherine Pui, Yin Mok, Éric Champagne, Natalie Burlone, Zeeshan Qadar, Teodoro Herbosa, Kevin Hung, Gleisse Ribeiro-Alves, Horacio Arruda, Pascal Michel, Ronald Law, Alain Poirier, Virginia Murray, Emily Chan, Nathalie Pignard-Cheynel, Sébastien Salerno, Grégoire Lits, Leen d’Haenens, Koen Matthys, and Mathieu Roy.

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are, necessarily, nominal variables, that is, there is no numerical logic behind the values of these variables. While they are rich and provide a nuanced understanding of the phenomenon under study, their analytical potential is limited. The statistics that can be derived from this process are descriptive only (frequencies and crosstab). Although the variables concerning the protagonists or groups and the discursive strategies of the journalists are also variables that require reflection by the analyst, we have formulated them, so their values are linked to their presence and, therefore, binary. One variable corresponds to each protagonist/group and to each discourse strategy and, for each of these variables, the analyst had to indicate whether it was absent (0) or present (1) in a given article. Thus, the values assigned to these variables come under a numerical logic, allowing certain additional analyses (e.g., fidelity and correlation tests). This being the case, the results presented in the following section, given that they are aimed at providing a picture of media coverage during the early stages of the pandemic in Canada, are based solely on descriptive statistics.

6  Canadian Coverage of the Onset of the Covid-19 Pandemic To answer our research question concerning the characteristics of the Covid-19 journalistic coverage during the first three months following the outbreak of the virus on Canadian soil, we will discuss several observations arising from the application of our analytical grid to the corpus under study. First, the sheer number of articles published by the selected daily newspapers during the period analyzed (40,436 articles that we had to sample) confirms the existence of a “media eclipse” (Lalancette & Lamy, 2020). The eclipse did not begin when the virus arrived in Canada (January 27), but rather after the WHO declared a global pandemic (March 11). Indeed, the study period appears to be split in two, with a drastic change in the density of coverage starting from March 11, 2020. The study period is composed of 13 weeks and, between January 27 and March 8, 2020 (i.e., during the first six weeks), only 11.6% (N = 587) of the articles were published. It was during the last seven weeks (March 9–April 27, 2020) that 88.4% of the articles in our corpus (N = 4468) came out. Transposing these proportions to the total number of articles published by the 20 daily

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newspapers reveals that, between March 9 and April 27, 2020, approximately 35,800 articles were put out by the daily newspapers to address the pandemic. The 20 selected daily newspapers published more than 5000 articles per week to inform Canadians about Covid-19. In light of this large volume of articles, the question which arose pertained to who wrote these texts. According to our analyses (see Fig. 6.1), most of the articles were by news journalists working for daily newspapers. However, almost a third of the articles were from a news agency. The most popular was Reuters, which accounted for 31.8% of these articles. Next, more than one in ten articles were written by an “editorial writer,” such as a columnist. Finally, more marginally, roughly 1 out of 20 texts were authored by an individual (or group) other than a news professional, for example, a letter to the editor or an open letter from a group of experts. 6.1   What Did the Articles on the Pandemic Contain? Our analytical grid made it possible to measure the preponderance of themes or protagonists in the articles that make up the corpus. Based on our coding process, it emerged that the articles for which the pandemic constitutes the main theme (N = 3639)8 put special focus on certain

6,2% News journalists

11,4%

News agencies 52,2%

Editorial writers

30,2% Non-news-professionals

Fig. 6.1  Authors of the articles (A total of 455 articles in the corpus did not mention the author) 8  A total of 1416 articles addressed the pandemic, not as their main theme, but as a secondary theme.

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subthemes. Statistically, the distribution of journalistic coverage of the pandemic, by its density, suggests four levels of prominence. The first level focuses on the theme of “The evolution of the virus in the population and in laboratories,” which is the main theme of 25.9% of the articles (N = 941). In other words, more than a quarter of the articles which addressed the pandemic as their main theme discussed, for example, case numbers and research on the virus. The second level contains two themes that accounted for 16.9% and 13.3% of the journalistic coverage, namely, the “economic slowdown” (N = 615) and “the interruption in the sports world” (N = 482). The third level addressed six themes that make up between 5.4% and 3.6% of the journalistic coverage, namely, the “application and reinforcement of preventive measures” (N  =  195), “borders, travel and travelers” (N = 160), “equipment for treating or preventing the virus” (N = 155), “difficulties facing the arts and entertainment” (N = 151), “mental health and loneliness” (N = 139), and “Canadian government financial assistance for citizens” (N = 131). The fourth level contains 16 other themes (see Table  6.2), which compose the remaining 18.4% (N = 670) of the journalistic coverage. While the effects of the COVID-19 pandemic have clearly been felt by all actors in society, the initial journalistic coverage of the crisis painted a picture in which certain protagonists or groups were especially impacted. According to their occurrence in the articles, the 19 protagonists or groups (see Table 6.1) can, in our view, be divided into three classes. To describe these actors, we borrow a theatrical metaphor, naming them: (1) the leads, (2) the understudies, and (3) the standbys. Indeed, we conceive journalistic articles as constructions that stage facets of the reality of the pandemic (Carignan & Huard, 2016; Petty et  al., 2002) and in which protagonists can play different roles. (1) Leads are protagonists or groups in the spotlight. They are ubiquitous in the initial coverage of the pandemic. According to our analyses, three protagonists or groups stand out as leads: individuals socially affected by the pandemic (present in 43.2% of the articles, N = 2183), individuals physically affected by the pandemic (present in 35.3% of articles, N  =  1782), and economic actors (present in 31.2% of the articles, N = 1578). (2) Understudies are protagonists or groups that are present, but less prominent, in the journalistic coverage. They generally play a secondary role to the leads, and they are less systematically present in the articles. However, understudies can rise up and take on a leading role in some

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specific cases. In total, we consider that nine protagonists or groups played understudy roles in the initial media coverage of the Covid-19 pandemic in Canada. They are health experts (present in 18.3% of the articles, N = 927), federal political stakeholders (present in 17.3% of the articles, N = 876), frontline workers (present in 16.2% of the articles, N = 821), sports stakeholders (present in 14.6% of the articles, N = 736), provincial political stakeholders (present in 14.4% of the articles, N = 726), humanities and social science experts (present in 13.5% of the articles, N = 682), public health departments in the various provinces (present in 13.2% of the articles, N = 668), cultural figures (present in 12.2% of the articles, N = 614), and the media (present in 12.2% of the articles, N = 614). Finally, (3) the standbys are the protagonists or groups with a fragmented presence in the journalistic articles. They are present at certain times, after certain events, but they are then scarcely present in subsequent news coverage. Their inclusion in the media agenda is not inherent to the daily life of the pandemic but conditioned on specific dynamics. According to our analyses, seven protagonists or groups can be considered standbys: populations at high-risk (present in 9.3% of the articles, N  =  470); the President of the United States (in office at the time), that is, Donald Trump (present in 6.4% of the articles, N  =  324), the World Health Organization (present in 6.1% of the articles, N = 306), the provincial and federal ministers of health (present in 5.7% of the articles, N = 288); law enforcement (present in 5.6% of the articles, N = 282); municipal political actors (present in 4% of the articles, N  =  200); and conspiracy groups (present in 1% of the articles, N = 49). 6.2   How Were the Journalistic Articles About the Pandemic Written? Although the ideals of journalistic practice historically prescribe ethical, neutral, and informative news coverage, contemporary practices are becoming more heterogeneous. Brin et  al. (2004) discuss the growing integration of “communication journalism.” Watine (2006) describes how journalistic practice has begun a gradual shift toward “conversational journalism.” This shift can be seen in “the gradual oralization of informative content […] the growing use of humor and derision […] the hyperbolization/sensationalization of the news […] the virtualization of discourse through a greater and greater use of figures of speech and second-degree references […] [and] the personification of news” (Watine, 2006,

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pp. 72–73, translated freely). Indeed, journalists and readers have become more familiar through these processes, which may help to make the news more accessible in terms of vocabulary and more appealing and entertaining in terms of their approach. This trend can be explained, in part, by the current economic situation of the media trying to attract readers to boost their advertising revenues and, consequently, by the media’s greater knowledge of the interests, values, and subjectivities of their audiences. What, then, can be said about the initial coverage of Covid-19—the crisis that so intensified individuals’ need for information? The results, after applying our grid, indicate that the main journalistic intention of the articles was to inform. A full 75.9% of the articles (N = 3837) show the main intention of providing an informative account of current events (N  =  3365) or presenting testimony in a neutral way (N = 472). Nevertheless, nearly a quarter of the articles, 23.5%,9 demonstrate a main intention other than to inform. Of these, 8.9% seek to raise readers’ awareness (N = 451); 8.2% seek to condemn or criticize an actor or situation (N = 413); 3% seek to reassure readers (N = 154); 1.6% seek to speculate about the pandemic (N = 80); 0.8% seek to sensationalize the situation (N = 42); 0.7% seek to instill fear or dread in readers (N = 37); and 0.2% seek to trivialize the situation (N = 13). We also explored journalists’ inclination to use direct and indirect quotations. As Charron (2006) noted in his study of the evolution of the use of quotations in political journalism, the use of direct quotes demonstrates a concern for neutrality, whereas the use of indirect quotes involves reappropriation and, hence, a greater share of subjectivity. This said, as Figs. 6.2 and 6.3 show, both strategies were used extensively in covering the early stages of the pandemic. Almost three-quarters of the articles contain direct quotations and more than two-thirds, indirect quotations. In other words, the articles simultaneously appear to lean toward staying neutral and toward reappropriating what is being said, for example by experts, in order to deliver it to readers in a different format. In addition, consistent with Watine’s (2006) argument that journalists are increasingly engaging in the “virtualization of discourse through a greater and greater use of figures of speech and second-degree references” (p. 73, translated freely), we used our grid to assess whether the articles revealed discursive strategies as a way of delivering a subjective portrayal of 9  About 0.6% of the articles (N = 28) were too brief to be able to determine a main intention.

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Fig. 6.2  Use of direct quotations 26% N=1,323

74% N=3,732

Present

Absent

Fig. 6.3  Use of indirect quotations

26% N=1,654 74% N=3,401

Present

Absent

the pandemic. This analysis is also consistent with Exemplification Theory (Zillmann, 1999), a theory of media influence stating that the media can use exemplars which “are essentially evocative words, phrases, images, and sometimes sounds that serve as cognitive shortcuts to glean meaning about complex ideas or situations” (Sellnow-Richmond et  al., 2018, p.  141). The use of exemplars is believed to allow the media to better capture the attention of the public and foster information retention (Zillmann, 1999).

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Along these lines, our analyses indicate that several subjective and image-focused strategies were employed in the initial coverage of the pandemic in Canada. In 13.9% of the articles (N = 704), the authors spoke directly to readers. In other words, they used the familiar “you” in an attempt to involve readers in the content of the articles, among other things to increase their sense of closeness to the news. Next, 13.8% of the articles show the use of metaphor or analogy. Using the analogy of war, for example, some authors provided readers with cognitive schemas with the aim (in this case) of stressing the gravity of the situation. In 11.7% of the articles, the authors engaged in self-staging, that is, they included themselves in the news item, for example, by using “I.” This strategy once again produces a greater sense of proximity, but this time between the author and readers (as opposed to between readers and the news per se). The use of comparison strategies was found in 6.9% of articles (N  =  347). For example, authors attempted to explain characteristics of the COVID-19 pandemic through comparisons with other health crises such as the H1N1 epidemic in 2009 or the Ebola crisis in 2014. Finally, 3.5% of the articles (N  =  175) contained strategies for personifying information. To solicit emotional reactions associated with receiving information, some article authors lent human characteristics to the information presented. For example, some articles might refer to the SARS-CoV-2 virus as a “silent killer” or “monster.”

7  Discussion In light of the portrait we have presented, an important question arose: Did the media coverage of the early stages of the pandemic in Canada contribute to effective communication about prevention in the face of the risks associated with the crisis? To respond (at least in part) to this question, we will base our discussion on the IDEA model for effective instructional risk and crisis messages (Sellnow & Sellnow, 2014), as presented in the introductory remarks of this chapter. This model proposes to evaluate risk and crisis messaging on the basis that they should contribute to “helping message recipients internalize the potential impact of the risk or crisis event, identifying appropriate channels and strategies for distributing the risk or crisis event messages, offering a brief and intelligible explanation of the nature of the risk or crisis, and providing specific self-protective action steps for people to take” (Sellnow et  al., 2017, p.  552). Hence, before addressing our general question, we explored four specific questions raised

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by the IDEA model: (1) Does the journalistic coverage facilitate “Internalization”? (2) Does the journalistic coverage facilitate “Distribution”? (3) Does the journalistic coverage facilitate “Explanation”? (4) Does the journalistic coverage facilitate “Action”? 7.1  Internalization With regard to Internalization, the journalistic articles made it explicit to members of the public that the pandemic concerned them directly and they were the first to be affected by its repercussions. Indeed, the protagonists/groups most often featured in the articles, which we consider as leads in the media representation of the crisis, were individuals socially or physically affected by the pandemic. Populations at heightened risk, such as older adults, people experiencing homelessness, or people with chronic or distressing illnesses (cancer, diabetes, respiratory disease, AIDS, etc.), were much less prominently featured in the initial news coverage. The fact that this group could be found in less than 10% of the articles (behind economic actors, sports actors, and cultural figures) is certainly problematic since, as we now know, specific populations have been the hardest hit by the pandemic. For example, according to data from the Institut national de santé publique du Québec (INSPQ), between January and September 2020, nearly 70% of Covid-19 casualties in Quebec were older adults living in residential and long-term care centers (CHSLDs). 7.2  Distribution With regard to Distribution, that is, the channels and strategies used to ensure that messages effectively reached the populations concerned, two elements seem worth pointing out: the type of article and the density of the journalistic coverage. In terms of article type, a wide majority (82.4%) of the articles analyzed were news pieces written by news professionals. As such, the messages were usually part of the news and figured prominently in the media analyzed: this increases the likelihood they will be consulted by readers. However, it should be noted that nearly one in five texts was not authored by a news professional (news journalist or news agency). This can create a context where “opinion” and “information” meld together, making it difficult for readers to sort out the two. Next, as mentioned, more than 40,000 articles were published by the 20 daily newspapers involved in this project, over a period of only three months. Thus, the

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Canadian press devoted the majority of its media space to the pandemic. Such coverage ensures that readers of these newspapers are exposed to the messages surrounding the health crisis. However, does such dense coverage—which can be described as a “media eclipse”—make for effective communication? As Lalancette and Lamy noted in their article on the effects of the Covid-19 media eclipse, “An overload of information can weary the public of a particular topic, which is counterproductive from a broad communication perspective” (online). It appears important in our view to approach the density of the initial coverage of the pandemic in a nuanced way: on the one hand, it may have heightened readers’ exposure to risk and crisis messages, but on the other, it may also have caused people to become overwhelmed or even desensitized to them. 7.3  Explanation With regard to Explanation, the criteria by which we analyzed journalistic articles are somewhat contradictory. On the one hand, as we have discussed, journalists generally operate under professional ideals that prescribe neutrality and information. On the other hand, effective risk and crisis messages “are strategically constructed to include appeals to affective and cognitive learning as the means to achieve desired behavioral learning outcomes” (Sellnow et  al., 2017, p.  555). The presence of journalistic intentions other than to inform in almost a quarter of the articles (23.5%), if contrary to journalistic ideals, indicates a wish on the part of journalists to go beyond their duty to inform and try to influence readers’ response. This could include, for example, seeking to raise their awareness or to frighten them. The use of discursive strategies to exemplify issues inherent to the pandemic, such as analogy, metaphor, or the personification of information, also suggests this wish to take part in crisis and risk communication during the pandemic. By capturing attention and facilitating information retention, cognitive shortcuts help, among other things, to advance understanding of pandemic-related information and, potentially, the use of this information for self-protective purposes. 7.4  Action Finally, in terms of Action, it is clear that the initial coverage of the pandemic in Canada was intended more to monitor and explain the crisis than to provide tools for readers to be able to take action to cope with it. In

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fact, only 5.4% of the articles (N = 195) featuring a main theme related to Covid-19 primarily dealt with the application or reinforcement of preventive measures (e.g., isolation or physical distancing) and 4.3% (N = 155) chiefly addressed equipment for treating or preventing the virus (e.g., hand disinfectant or masks). It appears to us that the initial coverage, which emerged abruptly and unexpectedly in mid-March, made readers more aware of the complex implications of the pandemic (by covering a wide variety of themes) as opposed to measures to curb its impact. In sum, it is our view that, through the messages it conveyed, the initial Canadian journalistic coverage of the pandemic had the potential to help “internalize” the crisis, to create a dense (perhaps overly dense) and legitimate “distribution” of information, and to promote “explanation” by using discursive strategies that were, nevertheless, seen as something to avoid in news journalism. However, the coverage shows little potential for “action” in that it puts very little emphasis on measures to enable readers to respond to the crisis.

8  Conclusion The media have a key role to play in crisis and risk communication (David & Carignan, 2017; Hanitzsch & Vos, 2018; Olsen et al., 2020), especially during a pandemic. By carrying Covid-19-related public health messages, Canadian daily newspapers contributed to distributing important information to the public. As a mainstream media, the Canadian print media has contributed to building Canadian society’s understanding of Covid-19. Our study, which focused on the media coverage of the first three months of the SARS-CoV-2 virus on Canadian soil, locates the major daily newspapers as key players in helping to mitigate the pandemic and its associated risks. The articles were intended, among other things, to familiarize Canadians with a new virus that was still largely unknown around the globe; the social, political, and economic issues arising from the pandemic; and the populations most concerned by pandemic risks and impacts. In addition, the articles often contained discursive strategies aimed at boosting appeal to readers and facilitating their understanding and retention of the information presented. This said, the messages conveyed by the articles, given what they contain and omit, as well as their density, also have limitations. In cross-­ referencing our findings against the IDEA model for effective instructional risk and crisis messages (Sellnow & Sellnow, 2014), it is apparent that

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newspaper messages have little potential to contribute to the “Internalization” of the crisis by certain high-risk groups (which are scarcely addressed in the articles) and that they focus very little on the “Actions” that individuals can take to protect themselves from pandemic-­ associated risks. The frantic pace at which articles were published also situates the Canadian press as a “Distribution” channel with ambiguous impacts that can potentially lead to discouraging the public (not to mention the impacts on the practices of journalists who are constantly declining in number and must increase their production because of cuts in the news sector). Moreover, the ideal of objectivity and neutrality, so intrinsically bound up with news journalism, is difficult to reconcile with the premise that risk and crisis messages should facilitate “Explanation” to the public, namely, by using strategies associated with exemplification theory. Our analyses reiterate the relevance of examining journalistic coverage to better understand risk and crisis communication in the context of a pandemic. They also highlight the impact of risk and crisis messaging as a central consideration for research. Indeed, while our study analyzed the messages (as opposed to their reception), in our view, the role of news stories in Canadians’ understanding of and response to the crisis is deserving of scholarly attention. Subsequent steps would be helpful in order to examine the reception and appropriation of the identified categories and types of journalistic messages. Given how temporality shapes risk and crisis communication (Sellnow & Seeger, 2021), it would be judicious to replicate our approach over a broader period than the first three months following the arrival of the SARS-CoV-2 virus on Canadian soil. At the time of writing, the pandemic is ongoing, and the current pandemic coverage appears considerably different from the initial coverage. In subsequent research, we will focus on how pandemic-related messages in the Canadian press have evolved over a one-year period.

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Petty, R.  E., Priester, J.  R., & Briñol, P. (2002). Mass media attitude change: Implications of the elaboration likelihood model of persuasion. In J. Bryant & D. Zillman (Eds.), Media effects: Advances in theory and research (pp. 155–198). Lawrence Erlbaum Associates. Radcliffe, D. (2020). COVID-19 has Ravaged American Newsrooms – Here’s why that matters ([SSRN Scholarly Paper] no ID 3693903). Social Science Research Network. https://doi.org/10.2139/ssrn.3693903 Seeger, T.  L., & Sellnow, M.  W. (2013). Theorizing crisis communication. Foundations of Communication Theory. Sellnow, D., Lane, D., Sellnow, T., & Littlefield, R. (2017). The IDEA model as a best practice for effective instructional risk and crisis communication. Communication Studies, 00(00), 1–16. https://doi.org/10.1080/10510974. 2017.1375535 Sellnow, T. L.. & Seeger, M. W. (2021). Theorizing crisis communication. Wiley-­ Blackwell, Publications of Communication Theory. Sellnow, D. D., & Sellnow, T. L. (2014). Risk communication: Instructional principles. In T. Thompson (Ed.), Encyclopedia of health communication (Vol. 17, pp. 1181–1184). Sage. Sellnow-Richmond, D., George, A., & Sellnow, D. (2018). An IDEA model analysis of instructional risk communication in the time of ebola. Journal of International Crisis and Risk Communication Research, 1(1), 135–167. https://doi.org/10.30658/jicrcr.1.1.7 Tejedor, S., Cervi, L., Tusa, F., Portales, M., & Zabotina, M. (2020). Information on the COVID-19 pandemic in daily newspapers’ front pages: Case study of Spain and Italy. International Journal of Environmental Research and Public Health, 17(17), 6330. https://doi.org/10.3390/ijerph17176330 Villena-Alarcón, E., & Caballero-Galeote, L. (2020). COVID-19 media coverage on Spanish Public TV. Tripodos, 2(47), 103–126. Watine, T. (2006). De la multiplication des procédés des procédés interactionnels dans les contenus de presse: Vers un journalisme de conversation. Les cahiers du journalisme, 16(34), 70–103. Winseck, D. (2018). Media and internet concentration in Canada 1984–2017. Canadian Media Concentration Research Project (CMCRP). https://doi. org/10.22215/cmcrp/2018.2. Zillmann, D. (1999). Exemplification theory: Judging the whole by some of its parts. Media Psychology, 1, 69–94. https://doi.org/10.1207/s1532785 xmep0101_5

CHAPTER 7

Disinformation in the Age of the Covid-19 Pandemic: How Does Belief in Fake News and Conspiracy Theories Affect Canadians’ Reactions to the Crisis? Marie-Eve Carignan, Olivier Champagne-Poirier, and Guilhem Aliaga 1   Introduction Following the outbreak of the Covid-19 pandemic in China in late 2019, the coronavirus rippled across societies the world over, causing tremendous health, social, and political upheavals. While every global crisis brings its share of uncertainty, the Covid-19 pandemic is a crisis without precedent in the history of modern societies. It poses a threat not only in Canada but around the world, in terms of health, economies, and social

M.-E. Carignan (*) • O. Champagne-Poirier Department of Communication, Université de Sherbrooke, Quebec, Canada e-mail: [email protected] G. Aliaga Université de Sherbrooke, Quebec, Canada e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. La Rocca et al. (eds.), Infodemic Disorder, https://doi.org/10.1007/978-3-031-13698-6_7

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well-being. According to the World Health Organization (WHO), this is the most serious health situation to be reported since 2005, when the global alert system for international public health emergencies was set up (WHO, 2020b). The world’s first known cases of the SARS-CoV2 coronavirus came to light in late December 2019 in the city of Wuhan, China, following initial reports by the Xi Jinping government. With the explosion in the number of infection cases and the presence of the coronavirus on all continents, the number of infected people quickly surpassed one million, reaching more than 5 million deaths1 directly attributable to Covid-19 by the end of 2021, that is, two years after the initial outbreak (AFP, 2021). In Canada, the first case of coronavirus was confirmed at the end of January 2020, by Public Health Canada (A.D.L.S.P., 2020). When infections exploded across the country, the Canadian government adopted public health measures to combat the coronavirus epidemic, such as screening, quarantine and isolation, vaccination, and travel restriction measures. Nevertheless, the number of variations and mutations of Covid-19 largely heightened its transmissibility and virulence, with considerable repercussions in Canada and worldwide (A.D.L.S.P., 2020). With the health crisis, the world turned quickly to news sites and the Internet, even resulting in a spike in traffic of up to 60% in some countries (OECD, 2020). The coronavirus pandemic context has likely changed the communication and information management of governments. In Canada, as in many countries, the population has been forced to get used to a new social normality that includes individual and collective health measures (Moreira Cesar et al., 2021). The Government of Canada has implemented the rapid and daily publication of open data (number of patients, screening and vaccination centers, precautions to take, safety instructions, emergency public aid, etc.), while also holding daily press conferences to inform the public of the epidemic’s evolution. The various actions put in place to communicate and transmit information have sought to reassure the public in a transparent manner. The rollout of Covid-19 alert and prevention apps, as well as commercials on social media and in traditional media, has likely prevented more casualties and infections (Ivanov, 2021). Even so, the disinformation published in some social and other media during the pandemic has 1  According to the WHO, the excess mortality directly and indirectly associated with SARS-CoV2 could be three times higher.

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weakened trust in governments, scientists, and the media, in addition to sowing confusion and undermining health protocols (WHO, 2020a). In this context, the authorities, as well as the media and journalists, have had to adapt in order to fight the proliferation of conspiracy theories and disinformation (Moreira Cesar et al., 2021). Before going any further, it is worth revisiting these two concepts. A conspiracy theory can be defined as a controversial belief that certain societal facts can be explained by the existence of a conspiracy or scheme (Dentith, 2014). There is nevertheless no consensus on the use of the term “theory” in this context, given that this is not organized knowledge that can be discussed rationally. Conspiracy theories are usually considered irrational, far-fetched, and paranoid beliefs (Carignan & Morin, 2022). As such, they constitute marginal knowledge that is even looked upon as being stigmatized by common sense, the elite, and the powers that be. This dismissal often nourishes conspiracy theories, as well as other stigmatized knowledge not necessarily involving conspiracies. The growth of this marginal knowledge underscores a social fragmentation in which some individuals think that we do not all live in the same reality. In other words, it is a belief in the existence of a real coordinated group, however large or small, acting in secret to further malicious intentions toward individuals, groups of individuals, or ethnicities (Dentith, 2014). Internationally and domestically, the emergence and development of conspiracy theories in the Covid-19 era have been very detrimental to public debate and citizens’ safety. The spread of conspiracy theories in social and other media is not a new phenomenon, but it is clear that conspiracy theories have become commonplace in public discourse with the appearance of the coronavirus (Rives, 2020). UNESCO and the European Commission (2021) have identified four generic conspiratorial beliefs about the coronavirus pandemic: (1) claims that the virus was artificially engineered (e.g., in a laboratory) by people with a vested interest (e.g., in reducing the world’s population); (2) theories that the virus was spread intentionally or that its natural spread was furthered by artificial means (such as 5G signals) to harm as many people as possible; (3) claims that vaccines and treatments were intentionally delayed in order to enable the spread of the virus and to harm as many people as possible; and (4) claims that certain health measures to curb the spread of the virus (such as vaccines and masks) are intentionally used to harm or control populations (Chaudet, 2020). Conspiracy theories thus feed on governments’ difficulty with or inability to manage the pandemic as well as on adherents’

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anxiety and distress (Carignan, Morin et al., 2022). This feeling is all the stronger in lockdowns when the breeding ground of uncertainty gives rise to fantasies surrounding various schemes (Jamin, 2009). The spread of the coronavirus around the world has been accompanied by an unprecedented wave of global disinformation. Disinformation or fake news refers to public or private news that is diverted from its original context, making it inaccurate, misleading, and erroneous (Monnier, 2020), or false information fabricated out of thin air that takes on the guise of real news in order to deceive people (FPJQ, 2019). Much of the misleading news that has emerged surrounding Covid-19 tends to point fingers at “the guilty”—often governments, political or scientific figures, or pharmaceutical industries (Monnier, 2020). The infodemic associated with the health crisis reaches its peak when the spread of fake news becomes a danger to the health of populations.2 The term “infodemic” refers to the massive profusion of information that is both scientifically proven and inaccurate on a given topic. In this context, it becomes difficult for the population to make out the facts. Along these lines, many people have speculated about the origins of the coronavirus on the Internet. Sharing of false news will tend to increase when the misleading information is accompanied by fake documents, photos, or videos that are taken out of context. This is a communicative ploy often used by adherents of conspiracy theories, which goes to show how the two phenomena (fake news and the inclusion of fake documents) can be interrelated (Breteau, 2018; Crawford, 2020). One of the most shared items of fake news associated with the pandemic has been the perceived danger of a potential Covid-19 vaccination program (Fondation Jean-Jaurès, Conspiracy Watch, Ifop, 2020). Other misleading information has also emerged, including the effectiveness of chlorine or UV light in curing coronavirus infections. Often shared on social media, conspiracy theories and fake news arising from the health crisis attempt to highlight some element of truth. Support from a member of a scientific community or someone perceived as legitimate will result in a perceived validation of the theory (Belghit, 2017). In the case of the coronavirus, conspiracy theories asserted with certainty are fueled by a lack of knowledge about the origin of the pandemic, and challenge the official discourse (Chaudet, 2020).

2  A loss of trust in the media and governments can lead to a reluctance to use diagnostic tests, or compromise vaccine campaigns and promotion (FranceInfo, April 2, 2021).

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In the present study, in connection with these theoretical observations regarding (1) mistrust, (2) news habits, and (3) attitudes toward social and health measures associated with Covid-19, we wish to assess how beliefs in fake news and conspiracy theories impact the reaction of the Canadian population to the coronavirus pandemic. Specifically, the analyses presented in this chapter aim to answer the following research questions and to confirm or refute their associated hypotheses. Our hypotheses are deduced from the theoretical elements presented above. Q1. To what extent have pandemic-related conspiracy theories and fake news permeated the beliefs of Canadian respondents? Q2. What are the socio-demographic characteristics of the Canadian respondents who subscribe to pandemic-related conspiracy theories and fake news? Q3. What are the sources used by the Canadian respondents who subscribe to pandemic-related conspiracy theories and fake news in order to learn about the pandemic? Hypothesis  The Canadian respondents who subscribe to pandemic-related conspiracy theories and fake news will be overrepresented among the users of social media and the Internet. Q4. What are the social attitudes of the Canadian respondents who subscribe to pandemic-related conspiracy theories and fake news? Hypothesis  The Canadian respondents who subscribe to pandemic-related conspiracy theories and fake news will be less favorable to the social and health measures put in place to limit the spread of the virus and will be more suspicious of political, scientific, and media authorities.

2   Methodology The project discussed in this chapter falls under a broader research initiative entitled: The role of communication strategies and media discourse in shaping psychological and behavioural response to the COVID-19 outbreak funded by the Canadian Institutes of Health Research.3 This initiative 3  This global grant initiative is led by Professor Mélissa Généreux. The first authors of this chapter are among the co-applicants of the grant.

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brings together international researchers from multiple disciplines, including community health, psychology, political science, and communications. As part of this major initiative, a population-based questionnaire survey was conducted to gain a better understanding of the impact of the pandemic on Canadians. The data collected during this survey will allow us to answer our research questions and test our hypotheses. In concrete terms, the questionnaire was developed using the Knowledge–Attitude–Practice model (Bettinghaus, 1986). It thus brings together broad multidisciplinary considerations ranging from strategies mobilized to learn about the pandemic to level of anxiety experienced (De Coninck et al., 2021). As is usually the case with a population-based survey, the questionnaire also identifies the socio-demographic characteristics of the respondents. We secured the authorization of the CIUSSS de l’Estrie-CHUS Research Ethics Board (#ref.: 2020–3674) in order to conduct this study. In terms of its form, the survey is a self-administered web questionnaire composed only of close-ended questions and requiring an average completion time of 18 minutes. The respondents were recruited by the Leger polling firm between November 6 and 18, 2020. The questionnaire was administered to Canadians 18 years of age and above who were randomly selected from the LEO panel (acronym for Léger Opinion) comprising over 400,000 members. In all, 2004 respondents completed the questionnaire. 2.1   Measurements and Analysis The analyses presented in this chapter, insofar as they are tinted by a resolutely communicational perspective, address only some of the questionnaire components. Moreover, the nature of our questions prompted us to deploy a descriptive and correlational analysis plan. Our objectives were to (1) draw a portrait of belief in conspiracy theories and fake news surrounding the Covid-19 pandemic in Canada and (2) assess the associations between this belief and the socio-demographic, communication, and attitudinal characteristics of the respondents. 2.2   Belief in Pandemic-Related Conspiracy Theories To assess the extent to which the Canadian respondents subscribe to conspiracy theories related to the Covid-19 pandemic, we had to create our

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own “conspiracy index.” At the time of this project, there was no existing and proven index that we could use to this end. Of course, the pandemic is a new and sudden event, as are the conspiracy theories surrounding it. This being said, in constructing our index, we drew inspiration from conspiracy statements that have been used in surveys conducted by the Pew Research Center and by the Observatoire du conspirationnisme of the Fondation Jean-Jaurès (Fondation Jean-Jaurès, 2020). Specifically, we presented the respondents with the following five statements and asked them, on a scale of 1 to 10 (1 = completely disagree, 10 = completely agree), to rate the extent to which they agreed with each statement. 1. I believe that my government is hiding important information about the coronavirus. 2. I believe the coronavirus was made intentionally in a laboratory. 3. I believe the coronavirus was made by mistake in a laboratory. 4. I believe that the pharmaceutical industry is involved in the spread of the coronavirus. 5. I believe there is a link between 5G technology and the coronavirus. A reliability test between the answers to the five statements yielded a Cronbach’s Alpha of 0.855. This high coefficient prompted us to create a “conspiracy index” whose score is created by the sum of the scores for the five statements. The maximum score for the index is 50, and the minimum score, 5. Thus, a respondent indicating that they “completely disagree [1/10]” with all five statements would score 5/50 on our “conspiracy index.” 2.3   Belief in Pandemic-Related Fake News The same dynamic observed for conspiracy theories also applies to pandemic-­related fake news: At the time of conducting this research, no tested and proven index from the scholarly community was available. In creating such an index ourselves, we found inspiration this time in the Mythbuster platform created and managed by the WHO, which aims, among other things, to combat false news surrounding the pandemic (WHO, 2020). We produced six statements related to what the WHO recognized (at the time of developing the questionnaire) as being among the most widely circulating fake news about the virus. We asked the

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respondents, on a scale of 1 to 10 (1 = completely disagree, 10 = completely agree), to what extent they agreed with each of the following statements: . I believe the coronavirus is not transmitted in warm countries. 1 2. I believe that the coronavirus primarily infects people over the age of 55 years. 3. I believe that the coronavirus is no more dangerous than the seasonal flu (influenza). 4. I believe that the sun or temperatures higher than 25 °C prevent the coronavirus disease (COVID-19). 5. I believe that the new coronavirus can be transmitted through mosquito bites. 6. I believe that spraying alcohol or chlorine all over my body will kill the new coronavirus. A reliability test between the answers to the six statements provided a Cronbach’s Alpha of 0.847. Once more, this high coefficient prompted us to create an index, this time the “fake news index,” whose score is created by the sum of the scores for the six statements. The maximum score for the index is 60, and the minimum score, 6. Thus, a respondent indicating that they “completely agree [10/10]” with the six statements would score 60/60 on our “fake news index.” 2.4   Sociodemographic Variables The questionnaire asked respondents to disclose several elements that would help paint a portrait of their sociodemographic characteristics. Specifically, they were asked to disclose their gender, age, and highest diploma: (1) elementary diploma or less; (2) high school or vocational diploma; (3) college diploma; (4) university certificate; (5) university bachelor’s diploma; (6) university master’s diploma; (7) university doctoral diploma; and (8) whether they were born in Canada or another country.

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2.5   News Habits The respondents were asked to rate the extent to which they use different sources to get informed about the Covid-19 pandemic. For each source, the Canadian respondents were asked to indicate whether they used it (1) always, (2) often, (3) rarely/sometimes, or (4) never. The sources they were asked to report on were television, print media, radio, government press conferences, their interpersonal networks (people close to them), social networking sites, and the Internet (excluding social networking sites). 2.6   Attitudes Toward Social and Health Measures, Experts, Authorities, and the Media In the course of this project, we sought to better understand relationships between belief in pandemic-related conspiracy theories or fake news and attitudes toward social and health measures and authorities working to mitigate the pandemic. In order to obtain data for these analyses, we asked the respondents, on a scale of 1 to 10 (1 = not compliant at all, 10 = fully compliant), to rate how consistent their life during the pandemic is with the health and social guidelines issued by Canadian authorities. They were also asked if they would be willing to receive the Covid-19 vaccine when it became available (at the time of the survey, the vaccine was not yet available to the general population in Canada). For this question, they were asked to indicate (1) yes, (2) no, or (3) undecided. Then, on a scale of 1 to 10 (1 = not at all confident, 10 = completely confident), we asked respondents to indicate the extent to which they trust the news media, politicians, government, health professionals, the Public Health Agency of Canada, and global public health organizations (e.g., the WHO). After running reliability tests, we opted for a “trust in political authorities” index (Cronbach’s Alpha = 0.910), which combines the trust scores toward politicians and the government (this index therefore has a minimum score of 2 and a maximum score of 20). We also opted for a “trust in health experts” index (Cronbach’s Alpha = 0.928) that combines scores for trust in health professionals, the Public Health Agency of Canada, and global public health organizations (this index thus has a minimum score of 3 and a maximum score of 30).

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3   What Proportion of the Canadian Respondents Believe Pandemic-Related Conspiracy Theories and Fake News? Before turning to the findings linking certain demographic and social characteristics to belief in pandemic-related conspiracy theories and fake news, it is important to provide an overview of the situation. First, it is important in this regard to describe the extent to which the survey respondents subscribe to the various components of our “conspiracy index” and “fake news index.” The phenomena we are attempting to shed light on with this approach are complex and multiform. For this reason, the assessment tools developed for the survey have several components that may generate different responses in respondents. As Fig. 7.1 shows, the Canadians surveyed do not perceive the five conspiracy statements presented to them in the same way. The mean score for the statement that appeared most credible, namely, that the government is withholding important information about the virus and the pandemic, is more than twice as high as the mean score for the statement that appeared least credible, that is, a connection exists between the development of 5G technology and coronavirus disease (4.8/10 vs. 2.3/10). It is therefore important to understand the tendency to believe in pandemic-related conspiracy theories in a nuanced way. Some theories are more easily accepted by the respondents than others. However, as the reliability test presented in the methodology (Cronbach’s Alpha = 0.855) demonstrates, there is indeed a trend. Belief (or lack thereof) in

Mean level of belief in the five conspiracy statements in the conspiracy index (N:2,004) 10 8 6 4 2 0

4.8

3.8

3.6

3.3

2.3

My government is The coronavirus was The coronavirus was The pharmaceutical There is a link between hiding important made intentionally in a made by mistake in a industry is involved in 5G technology and the information about the laboratory laboratory the spread of the coronavirus coronavirus coronavirus

Fig. 7.1  Mean level of belief in the five conspiracy statements

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Mean level of belief in the six fake news items in the fake news index (N:2,004) 10 9 8 7 6 5 4 3 2 1 0

2.3

3.3

3.4

3.1

2.8

2.3

The coronavirus is The coronavirus The coronavirus is The sun or The new Spraying alcohol or not transmitted in primarily infects no more dangerous temperatures higher coronavirus can be chlorine all over my warm countries people over the age than the seasonal than 25C degrees transmitted through body will kill the of 55 years flu (influenza) prevent the mosquito bites new coronavirus coronavirus disease (COVID-19)

Fig. 7.2  Mean level of belief in the six fake news items

one statement appears to be statistically associated with belief (or lack thereof) in the other statements. A similar dynamic can be seen in the case of the fake news submitted to the respondents. Some fake news items appear more credible than others (see Fig. 7.2). Thus, the most credible fake news to the respondents in November 2020, ten months after the virus arrived in Canada, is that coronavirus disease is less dangerous than influenza (3.4/10) and that individuals ages 55 and above are at greater risk of being infected by the virus than the rest of the population (3.3/10). The least credible news item is that the virus is not transmitted in warm countries (2.3/10) and that it is possible for an infected person to eliminate the coronavirus by applying alcohol or chlorine all over their body (2.3/10). This being said, it is important to note that the average levels of belief in the six fake news items are generally low, demonstrating that they have little impact on the respondents’ perceptions. Even so, as was the case for the conspiracy theories, a trend can be observed between adhesion to the six fake news stories (Cronbach’s Alpha = 0.847). Once more, belief (or lack thereof) in one fake news item appears to be statistically associated with belief (or lack thereof) in the other fake news items. Given that belief in conspiracy theories and fake news constitutes a system of mutually influential elements, we sought to assess the proportions in which Canadian respondents generally or strongly adhere to these systems. By combining the scores for the different components of our indices, we established “belief thresholds.” The first indicates a threshold

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grouping together respondents who generally agree more with the components of the indices than they disagree with them. The second indicates a threshold grouping together respondents who strongly agree with the components of the indices. Table 7.1 shows the thresholds that were used. The average scores are 17.9/50 (SD:10.4) for the conspiracy index and 17.3/60 (SD:10.9) for the fake news index. The use of threshold segmentation provides some insight into the standard deviations of the indices. Figure 7.3 shows that a very marginal proportion of individuals strongly adhere to the indices. General belief is more common. Figure 7.3 reveals that the proportion of respondents generally adhering to conspiracy theories is much greater than the proportion believing in fake news (23.5% vs. 11.1%). It also puts into perspective the low presence of “strong belief” among the respondents. Nevertheless, the fact that nearly one in four respondents generally subscribed to the “conspiracy index” shows that the rise of conspiracy theories amid the pandemic is a worrying phenomenon that is far from isolated. Finally, while the numbers for the two indices differ in many ways, our correlational analyses show a strong association between the scores on the Table 7.1  Index thresholds Conspiracy index (maximum score of 50/50)

General belief

Scores of 26/50 and +

Strong belief

Scores of 41/50 and +

Fake news index (maximum score of 60/60)

General belief

Scores of 31/60 and +

Strong belief

Scores of 49/60 and +

Percentage of Canadian respondents who generally or strongly agree with the indices Strongly believes in fake news in the fakenews index (n:39) Generally believes in fake news in the fakenews index (n:222) Strongly believes in the theories in the conspiracy index (n:62)

1.9% 11.1% 3.1%

Generally believes in conspiracy theories (n:470) 0%

23.5% 5%

10%

15%

20%

Fig. 7.3  Distribution of the respondents according to the thresholds

25%

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indices (r = 0.696, p = 0.00). Indeed, the higher a respondent scores on the fake news index, the more likely they are to score high on the conspiracy index (and vice versa). This correlation coefficient suggests the existence of similar thought patterns behind belief in fake news and conspiracy theories. The following analyses will determine whether these patterns are associated with socio-demographic, news, or attitudinal traits. 3.1   Are Certain Socio-demographic Characteristics of the Respondents Associated with Belief in Pandemic-Related Conspiracy Theories and Fake News? As regards respondents’ sociodemographic traits, we found significant associations between belief in the indices and the respondents’ gender. Men adhere slightly more strongly than women to the statements making up our conspiracy index (r = −0.045, p