Quantified Storytelling: A Narrative Analysis of Metrics on Social Media [1st ed.] 9783030480738, 9783030480745

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Quantified Storytelling A Narrative Analysis of Metrics on Social Media

Alex Georgakopoulou Stefan Iversen Carsten Stage

Quantified Storytelling

Alex Georgakopoulou • Stefan Iversen Carsten Stage

Quantified Storytelling A Narrative Analysis of Metrics on Social Media

Alex Georgakopoulou School of Education, Communication & Society King’s College London London, UK

Stefan Iversen School of Communication and Culture Aarhus University Aarhus, Denmark

Carsten Stage School of Communication and Culture Aarhus University Aarhus, Denmark

ISBN 978-3-030-48073-8    ISBN 978-3-030-48074-5 (eBook) https://doi.org/10.1007/978-3-030-48074-5 © The Editor(s) (if applicable) and The Author(s) 2020 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. Cover pattern © John Rawsterne/patternhead.com This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Acknowledgements

A panel on ‘Narrative and Metrics on Social Media’, which we co-­ organized as part of the Narrative Matters conference, 2018, The Netherlands, served as the first step towards putting on the map of narrative studies this under-represented area and towards beginning to engage in productive conversations with colleagues and students. We are grateful to all those—too many to mention by name—who indulged us in the Narrative Matters conference and numerous workshops since then. We are also grateful to the anonymous reviewers for their very helpful comments on the book’s proposal with the usual proviso that all remaining errors are ours, and to our Commissioning Editor Cathy Scott for believing in this project. Finally, our thanks go to Dr Anda Drasovean for help with the final editing stages of the book.

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Contents

1 Analysing Quantified Stories on Social Media  1 1.1 Narrating Numbers  1 1.2 Social Media, Metrics and Numbers  4 A History of Metrics and Numbers   6 Quantified Self-Tracking   7 Metrics and Affect   9 Visibility and Social Buttons  10 1.3 Stories on Social Media 12 ‘New’ Types of Stories, ‘New’ Types of Telling?  16 Storytelling Participation Between Agency and Media Affordances  17 1.4 Quantified Storytelling: Our Approach 19 Questions and Methodology  19 A Heuristic Typology of (In)Visible Metrics  21 Key-Insights: Metricized Formats, Engagement and Power  22 References 25 2 Measuring and Narrating the Disrupted Self on Instagram 31 2.1 Introduction 31 2.2 The Quantification of Illness Narratives on Instagram 34 2.3 Methods and Material 38

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2.4 Analysis 40 Stories of Teleological Counting and Hope  40 Stories of Frustrated (Re)Counting  44 Performative Measures of Positivity and the Tellability Crisis of Having Nothing to Count  47 2.5 Conclusion 53 References 55 3 Making Memes Count: Platformed Rallying on Reddit 61 3.1 Introduction 61 3.2 The Metricized Affordances of Reddit 62 3.3 Methods and Material 68 3.4 Analysis 75 Meta-memetics  75 Political Education  80 Outreach and Influx  81 3.5 Conclusion 84 References 88 4 Curating Stories: Curating Metrics—Directives in the Design of Stories 95 4.1 Introducing Stories as Designed Features 95 4.2 Directives in the Design of Metricized Stories 98 4.3 Material and Methods100 A Critical, ‘Values in Design’, Perspective 100 Tracking the Design of Stories 102 Corpus-Assisted Methods 103 Communicative Practices: A Case Study of Influencers’ Stories 105 4.4 Analysis106 Directive I: Sharing-Life-in-the-Moment 106 Directive II: Audience Engagement as Quantified Viewing 112 Directive III: Authenticity in Tellers’ Self-Presentation 119 4.5 Conclusion124 References128

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5 Conclusion133 5.1 Stories Through the Lens of Content, Interface and Algorithmic Metrics133 Tellability as Narrative Value 137 Multivalent Platforms and the Problem of Public Value 140 Reactive Agency? 141 References142 Index145

List of Figures

Fig. 4.1 Fig. 4.2 Fig. 4.3 Fig. 4.4 Fig. 4.5 Fig. 4.6 Fig. 4.7

Distribution of online articles about the Story feature over time (May 9, 2012–January 30, 2018) NVivo coding of Lele Pons’ stories Example concordance lines for view and watch + quantifying expressions (e.g. ‘how many’) Semantic field of ‘rate’ Semantic field of ‘engagement’ Semantic field of ‘creative’ (as word cloud) Example concordance lines for ‘authentic’

104 111 116 117 118 119 121

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List of Tables

Table 2.1 Table 2.2 Table 3.1 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 4.5

Number of posts, comments, hearts and views on the three Instagram profiles, which are analysed in the chapter 38 The ten most Liked posts on the profile Jannelivsnyder66 49 Number of upvotes and comments on the ten most commented-upon posts on r/The_Donald from February 20, 2016, to February 29, 2016 75 Partial word sketch for moment107 Most salient verbs that take story as an object in the Ego-Media Stories, British National Corpus, English Web 2015 and TED_en corpora 108 20 most salient semantic domains in the Ego-Media corpus and most frequent words assigned to them 109 Verb collocates of ‘story’ 115 Top 10 collocates for ‘authentic’ (ranked by logDice score) 121

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CHAPTER 1

Analysing Quantified Stories on Social Media

1.1   Narrating Numbers In November 2019, Instagram announced an experiment with a segment of profiles where the Like score was to be visible only to the profile owner/ poster and not to followers. This initiative was explained by Adam Mosseri, head of Instagram, as an attempt to ‘depressurize’ the platform, tone down popularity evaluation among users and thereby help to support mental health. Removing barriers for sharing ‘the ordinary’, and ultimately for extracting more knowledge about users, could however be seen as a less altruistic motivation. Although the long-term consequences and implications of this experiment are difficult to foresee at this point, it nevertheless seems to indicate that social media platforms are beginning to acknowledge the widely circulating critique of their heavy reliance on metricizing social relations and interactions. The crux of the critique is that such metricization renders communication too restrained, too polished and too overtly preoccupied with comparison and social performance. The visible quantification of shared content and storytelling has created a sociality of comparative assessment, which is not always healthy for humans—and maybe also not for business, at least if we read Mosseri’s statement as an effort to ensure that more users will share their more or less mundane stories on Instagram. In a world where everything and everybody is ranked, super-popular subjects and highly rated individuals, such as Influencers, can ironically also end up having the kind of power that takes power away from a social © The Author(s) 2020 A. Georgakopoulou et al., Quantified Storytelling, https://doi.org/10.1007/978-3-030-48074-5_1

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media platform that enabled them with its metrics to become popular in the first place. Consider Influencer Kylie Jenner’s (cf. 25 million followers on Twitter) tweet back in February 2018 about Snapchat: ‘sooo does anyone else not open Snapchat anymore? Or is it just me… ugh this is so sad’ (Jenner 2018). Seen from one perspective, this tweet was but one among many in the social media posts of an internet celebrity. From another perspective, however, this particular narrative came with extraordinary consequences. Subsequently to the tweet, the stock of Snapchat began to fall, and it continued to drop by over 6% through to the following day. That added up to a roughly $1.5 billion loss in market value, according to Reuters.1 Numbers and measurements have also become crucial aspects of the actual stories shared on social media and their mobilization of users and action. In the summer of 2019, 13-year-old Marcus from Denmark was diagnosed with a rare brain tumour. The tumour could not be treated in his home country. It could be treated in the United States, but in order to initiate this treatment, 4 million Danish kroner (approximately €530,000) was needed, of which Marcus and his family had none. His friends decided to raise the money by collecting bottles, each paying 1 krone. The initiative reached broadcast media and spread from there to social media as a story of childhood friendship that mobilized people to help. Over a short period of time, 30,000 people became members of a Facebook group, sharing the collective goal of amassing the funds needed. They succeeded in crowdfunding the money in less than a month, and the story’s unfolding and development became highly entangled with numbers and counting: the story ended when the total figure sought for the treatment was achieved. Numbers can also generate content in more playful ways. Anyone in contact with the YouTube platform will probably have encountered what is known as ‘challenges’, where the poster engages in various types of often bodily experiments or social games such as eating weird combinations of food without vomiting, pranking friends and relatives or performing tricks that are unlikely to succeed. One popular format is what is known as the 100 layers or 100 coats challenge (YouTuber ‘Simply Nailogical’’s ‘100 coats of nail polish’ has 25 million views). To complete it, one must cover oneself in 100 layers of, say, foundation or pieces of clothing. Each process becomes a shareable story, and the format of the challenge decides its distribution of excitement: each layer furthers the plot by bringing the ending one step closer as the story is quite literally a

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story about a process counting. This challenge has no particular purpose besides staging experiments that make users laugh—by, for example, being difficult, going wrong, restraining the body—and creating or maintaining relationships between YouTubers and their subscribers. These four examples offer glimpses of emerging relationships and feedback loops between stories, numbers and value production on social media platforms, but also of shifting levels of users’ agentive influence on platformed communication. The 100 layers challenge combines storytelling and counting in a format that bodes well with the engagement design of the YouTube platform and offers avenues for personal expression and positive connections while generating trackable value in the form of engagement on the platform and, ultimately, options for advertising. The crowdfunding activity around Marcus, the Danish boy, is made possible by the story of the numbers generated by the activity. Not only are Jenner’s storytelling practices nested in and conforming to a platform whose interface lets her value materialize in the form of a number (25 million followers); the stories she tells may, in turn, affect the value of other platforms. And Instagram’s experiment with the visibility of the Like score shows that social media measurements shape social relations and human communication in fundamental and sometimes disturbing ways and that platforms continuously transform and innovate in order to motivate as much commodifiable user activity as possible. All the above cases are premised on how storytelling on social media platforms is intertwined with a ubiquity of numbers, metrics and rankings. In this book, we set out to explore stories as quantified activities on social media, aiming to show how the multiple levels of quantification that communication on digital platforms is subjected to have profound consequences for what stories can be told, distributed, become available and how, how stories are engaged with and how tellers present themselves and their lives through stories. Our analyses will address the following questions: • How and to what extent is quantification oriented to and constitutive of a story’s plot and ways of telling? How do metrics create preferential conditions (or directives) for the telling of specific stories about specific types of experience, both about mundane, everyday life and about complications?

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• What stories, lives and types of self become more or less (in)visible and available on platforms as a result of what processes and practices of quantification? What is the role of power-users in this? • How do metrics facilitate and promote the distribution and mobilization of specific stories as vehicles for community (re)formation and belonging? What is the role of users’ creative (re)workings of stories in this? • How do metrics shape the ways in which stories are designed and launched by platforms and equally shared and engaged with by audiences? Through addressing the above questions, we aim to bring to the fore the kinds of story tellability and values for the tellers that are foregrounded and sought after or equally silenced as a result of the quantification of stories. Our three cases represent different storytelling practices on different social media platforms: personal storytelling about illness on Instagram (Chap. 2), the use of stories in collective mobilization rhetoric on reddit (Chap. 3) and the design of stories as quantified activities with metrics becoming an integral part of their plot, telling and tellers’ self-­presentation on Snapchat and Instagram (Chap. 4). The purpose of this introductory chapter is twofold. Because of the interdisciplinary nature of our questions and interests, we find it necessary to go to some length in situating our approach in relation to two largely distinct bodies of work: ‘social media metricization and quantification’ (Sect. 1.2) and ‘stories on social media’ (Sect. 1.3). Section 1.2 looks into recent work in media studies and sociology on metricization, quantification and social media platforms. Section 1.3 looks at recent work in narrative studies on interdependencies between engagement with social media platforms and storytelling practices. Drawing on this existing work we will then outline the basic assumptions underlying our approach towards an understanding of quantified storytelling by returning to our research questions, methods and assumptions in greater detail (Sect. 1.4).

1.2   Social Media, Metrics and Numbers A key-feature of social media platforms is their metricization (Lupton 2016; Marres 2017) of social activities and communication through continuous measurements of interaction and behaviour with various forms of visible and invisible counting, scoring and tracking. Each platform comes

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with a particular set of metrics that measure and shape relations between personal profile identifiers, particular types of (inter)activity and what becomes visible in particular feeds (McCosker 2017). This is often referred to as a process of datafication, which produces knowledge that can also be aggregated and put to use in other contexts often unknown to users (van Dijck 2013). In The Platform Society (2018), Dijck, Poell and Waal tellingly define an online platform as: a programmable digital architecture designed to organize interactions between users—not just end users but also corporate entities and public bodies. It is geared toward the systematic collection, algorithmic processing, circulation, and monetization of user data. (van Dijck et al. 2018, 4)

Their concept of ‘the platform society’ furthermore designates how online platforms—particularly those controlled by the ‘Big Five’ (cf. Google, Facebook, Apple, Amazon, Microsoft)—are becoming intimately intertwined with social structures in the sense that key-institutions and cultural practices are increasingly relying on and moulded by corporate platforms and their three basic mechanisms: the datafication of user behaviour, the commodification of this data and the selection or curation of information presented to users based on previously collected data (van Dijck et al. 2018, 32). The roles of quantification on these platforms are multi-faceted. In this book, we define, for the purpose of our analyses, the interchangeable concepts of quantification and metricization in the following way (Lupton 2016; Marres 2017): ‘Quantification’ is deployed to describe numerical measurements (e.g. quantifying the body by using a weighing scale to get to know it through numbers and their development over time). In order to quantify (measure or count) ‘beings’ in the world (Brighenti 2018, 28), you need categories or units. ‘Metrics’ designate the more or less standardized systems of units that can be used to measure or count these beings (e.g. using ‘metre’ to measure length, ‘kilogram’ to measure mass and ‘second’ to measure time—or ‘Likes’ to measure communicative response). The process of establishing and using a metric system to be able to measure aspects of the world, we refer to as ‘metricization’. Following this, we claim that storytelling is currently ‘metricized’ and ‘quantified’ in new ways due to the metrics being introduced by and used on social media platforms. As an example, the quantification of human communication on Facebook relies on a range of (opaque) metrics that make it possible to,

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for example, measure and count how often, for how long, in what order and in what location communication takes place. Following this, ‘quantified storytelling’ refers to storytelling practices that take up, or are measured according to, different metrics whereby numbers and counting are integrated into the act of telling stories. A History of Metrics and Numbers A key-interest in sociological, historical, media and cultural studies research on metrics and numbers has been the importance of standardized metrics for developing effective societies based on trust and for shaping cultural understandings of legitimate and valuable practices. The premise of such studies has been that the social power of numbers relies on their reputation as objective, transparent, impersonal and apolitical tools able to create disinterested evidence of beings in the world. However, while standardized measures may allow for certain types of action to take place (e.g. trade across larger distances), they also support the increase of practices that can be measured according to particular standard metrics: ‘Accounting systems and production processes are mutually dependent’, as stated by Porter (1996, 43). You simply get what you measure because what can be measured counts (Badiou 2008; Gerlitz 2016). Particular forms of quantification are thus always part of specific ‘measurement regimes’ (Porter 1996, 33), because metrics support certain goals and logics in terms of shaping actions and procedures. The use of numbers for several core social practices such as counting money, measuring nature or making lists is ancient (Staeheli 2012). Michael Power, for instance, argues that in the thirteenth century, these tools were ‘to be found in the “social laboratories” of markets, gambling houses, merchants’ ledgers, artists’ studios, naval dockyards and in the twilight world of alchemy’ (Power 2004, 766). In the eighteenth century, a ‘new emphasis on precision in measurement’ evolved based on innovations such as the thermometer, clock and barometer (Power 2004, 766) and on a wish to provide societies with reliable information and procedures for administration and control based on a ‘need to establish agreement, credibility and trust’ in the increasingly complex and industrialized nation states of the time (Power 2004, 766). In the nineteenth century, an urge to statistically measure the developments of whole societies in terms of census surveys and statistics of life and death was prominent, while the twentieth century introduced macro-economic models, where societies’

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economic developments could be measured and predicted, but also a range of tools to micro-manage performances inside large formal organizations. The twenty-first century—to add to Power’s historical overview—is the era where real-time and large-scale aggregation of measurements of individual everyday practices become culturally important due to digital technologies and platforms. The ‘measurement regime’ introduced by digital media is thus connected to the epoch of performance measurement described by Power, but also diversifies it by measuring evermore dimensions of the personal, social and biological processes of everyday life. In that sense, measurements become increasingly mundane—and the mundane becomes increasingly measurable. This also includes the act of telling a story, which is today increasingly taking place in media environments affording and performing various forms of measurement and quantification. As we will show in this book, stories on social media therefore increasingly integrate numerical logics while also being circulated and sequenced based on processes of both user-driven/visible and algorithmic/invisible measurement and of both first-order and second-order measurements. First-order measurements refer to the operation that allows us to count certain units due to the construction of metrics, while second-­ order measurements are linked to the actual processes of counting, comparing, listing and tracing developments (Power 2004). New buttons on Facebook, for instance, introduce changes on a first-order level, while the multiple operations of (more or less invisible) counting and comparing the use of these buttons belong to a second-order level. Social media have typically introduced a new set of first-order measures and metrics (e.g. Like, comment, share, retweet) that make it possible—through second-­ order calculations—to count social processes on a large scale and to make this counting profitable and economically valuable. Quantified Self-Tracking Media studies research dealing with how users of social media engage in practices of measurement in their communication have taken a particular interest in processes of tracking the self, the body and its biological transformations. Digital media scholar Richard Rogers has, for example, distinguished between ‘vanity metrics’, a type of metrics used to measure individuals and their social impact, and ‘alternative metrics’, which can be

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explored to understand broader processes of social mobilization around various societal issues (e.g. hashtag analytics) (Rogers 2018). Metrics have always been crucial for the definition and realization of cultural norms regarding the attractive, able or, equally, unwell body. Metrics and numbers are powerful not only because they are often perceived as truthful in terms of, for example, measuring the various dimensions of the body but also because they shape future actions by making these actions valuable within a certain logic of measurement. Crawford, Lingel and Karppi have, for instance, shown that the introduction of weighing scales in private homes and of standardized metrics for defining the weight of a normal body in the late nineteenth century produced a norm according to which future bodies were moulded, desired and produced. Being a body of a certain height and below a certain weight became culturally valuable through the dissemination of a specific metric system and new technologies for body measurement (the weighing scale; Crawford et  al. 2015). The growing interest in tracking processes of (re)shaping the body through digital technologies has also been framed as intertwined with bio-political processes of self-discipline, effectivization and constant evaluation that support a capitalist entrepreneurial agenda or an ‘ethos of neoliberalism’ (Ajana 2017, 1). Metrics have thus been understood as essential for positioning the self in a landscape of normative performance goals and expectations that it must then try to live up to. While some research has focused extensively on the relationship between metrics and the cultural reproduction of bodily and neoliberal norms, another research strand has supplemented this approach by exploring the historical continuities between pre-digital and digital forms of self-­ measurement and stressing how individuals actively play with or negotiate the meaning of the metrics they use. In her seminal book The Quantified Self (2016), Deborah Lupton has argued that engaging in self-­ quantification (e.g. through wearables, pedometers or mood trackers) is not only a tool for subjective improvement or progression as it can also be used to quantify the self in more or less humorous, artistic and unpredictable ways and that the data produced through self-tracking are often ‘lively’ and open to multiple appropriations (Lupton 2016). Neff and Nafus (2016) furthermore stress subjective agency in self-measurement by distinguishing between different self-measurement strategies: self-tracking (where the aim is to transform/reach a goal), life-logging (where the main goal is to self-reflect), and self-experimentation (where the main goal is to investigate the subjective effects of experimentation).

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Metrics and Affect Pantzar and Ruckenstein’s research on digital self-measurement has also shown that self-trackers’ engagement with metrics is far from as objective, or raised above subjective concerns, as the mere numbers and curves produced by these practices of measurement might seem to suggest. Self-­ trackers translate ‘measurements to fit their expectations and experiences of day-to-day life and define the value and importance of measurements in a manner that complies with their purposes and self-understandings’ (Pantzar and Ruckenstein 2017, 2). This implies that self-measurements often distance themselves from notions of ‘mechanical objectivity’ in favour of a more contextualized notion of ‘situated objectivity’ (Pantzar and Ruckenstein 2017, 2), whereas affect plays a more crucial role due to the fact that in ‘measurement data, bodies are reflected on in an experiential and emotive sense’, as users ‘feel the metrics’ about their bodies (Pantzar and Ruckenstein 2017, 8). Similarly, Lagerkvist has stressed the affective dimensions of numbers. Through interviews with bereaved families, she shows how high scores of comments or responses on social media after the death of a loved one can feel like a ‘confirmation through numbers’ (Lagerkvist 2018, 25), which alleviates feelings of loneliness, and how rising visitor statistics can be experienced as ‘pleasing’. A lack of response can, however, be perceived as cruel, while a continuously high level of interest can feel like ‘too much’ or as somehow fixating the bereaved in a state of despair. The affective dimension of less visible forms of algorithmic metrics2 on social media has been investigated by, among others, Bucher (2017) who, through interviews with media users, argues that these measurements spur a range of different affects during everyday encounters with platforms and apps: for example, a sense of unease or even offence, due to constantly being classified according to existing categories by the platforms; experiences of anger or amazement if the interface suddenly reveals knowledge about one’s desires which has not been communicated or searched for; annoyance or laughter when the algorithm ‘gets you wrong’ and offers something irrelevant; an ambivalent feeling of not wanting to care about Likes and numerical response, but still following and feeling them; moments of despair if the interface reminds you about hurtful events in the past (e.g. the death of a loved one); and irritation if the algorithm overexposes material from friends that you are not particularly interested in following on an everyday basis (Bucher 2017). In mapping these

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responses, Bucher stresses how users’ rising awareness of algorithms, and their growing attentiveness towards what she calls ‘the algorithmic imaginary’, is intertwined with a range of affective processes. In research that focuses more on the structuration of affective dimensions of metrics as opposed to the users’ subjective agency, metrics are argued to be powerful as ‘affective measures’ that do something to the bodies they quantify (Beer 2016, 189), for example, by motivating them to embrace risk and improve before being measured again. This implies that metrics also produce affects through processes of judging individual actions and performances as, more or less, valuable according to standard measures (Porter 1996, 45). Visibility and Social Buttons Another strand of research has focused less on the structure/agency nexus and more on the epistemic and relational aspects of metrics. Gerlitz and Rieder describe measures and metrics as ‘epistemic devices’ (Gerlitz and Rieder 2014) that create knowledge by breaking down worldly complexity and conditioning future forms of action. Brighenti adds to this by seeing measures as ‘an inherently relational device, one that defines relations of value and assembles disparate beings by bringing them into given configured relations within a defined environment’ (Brighenti 2018, 28). On this line of thought, metrics show and establish relations that allow us to compare and ascribe value to—and thus also to interpret and ‘visibilize’—specific qualities: ‘Making measures is a way of making meaning and, concurrently, of making meaning visible’ (Brighenti 2018, 28). Importantly, measurements do not simply represent the world or self but code them in certain ways (Porter 1996, 43). In doing this, measures reduce complex matters to simple categories and thus tend to present the world as overtly orderly and structured (Porter 1996, 85). Research on metrics has also explored the performative relationship between value, measurement and social media based on the premise that ‘values’ should not only be understood as static qualities of phenomena in the world but also as something produced through performative processes of mediation (Gerlitz and Lury 2014). The interface logics of social media platforms has been put under scrutiny in this respect. The double role of buttons on social media interfaces (e.g. the Like or heart button) in representing and shaping social processes has been highlighted by scholars such as Carolin Gerlitz, Celia Lury and Anne Helmond. Gerlitz and Helmond

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have specifically theorized the Like on Facebook as a ‘social button’ with the double capacity ‘to instantly metrify and intensify user affects—turning them into numbers in the Like counter—while fostering further user engagement (…)’ (2013, 1350). The act of measurement through social buttons has thus been argued to reposition the measured in a way that changes or does something to it—for example, by ascribing more or less value compared with other social entities. Liking a post, for instance, does not only ‘reveal’ that someone appreciates the post but also turns it into a ‘Liked post’ with a different value and circulatory force on the social media platform. In this line of research, the concept of ‘multivalence’ has been used in order to highlight the multiple values created simultaneously on social media (Gerlitz 2016; Marres 2012). When a patient, for instance, shares a story on Instagram—and it is shared further by her followers—multiple forms of value are potentially enacted: affective-psychological values linked to the act of narration, social values linked to collective support and empathy, attention/circulation values linked to pushing the heart button, which registers the Like but also distributes the content further in the network (Gerlitz and Helmond 2013), economic value linked to various forms of datafication and so on. Research on metrics and digital/social media encompasses investigations of users’ agentive and affective engagement with measurement tools, medium-specific explorations of platform logics and buttons and sociological accounts of the intertwinement of quantification with neoliberal, entrepreneurial and capitalist ideologies. The often-employed concept of multivalence helps us to understand and acknowledge that despite data scandals and processes of corporatization, users still engage with social media platforms to perform activities that hold affective, existential and social value for them (Lagerkvist 2017). At the same time, it is notable that while early research on social media participation focused on its democratic potentials and new opportunities for users to obtain a voice (Benkler 2006; Bruns 2008; Jenkins 2006), recent research has increasingly highlighted how social media confront and deconstruct democratic logics and principles in favour of corporate and capitalist ones (Dijck et al. 2018). The role of metrics and quantification is key to this growing critical pursuit. Our approach to metrics and social media storytelling in this book will acknowledge this tension and ambivalence in the literature between agency-focused and structure-focused positions, and we will investigate material that prioritizes agency and structuration to varying degrees. At

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the same time, we will also stress that analytical boundaries between user-­ generated content, interface logics and algorithmic processing are highly porous. Keeping these ambivalences, tensions and porous boundaries in mind, we now move from our survey of existing work on quantification, metricization and digital platforms to our survey of existing work in narrative studies on storytelling and social media. Even as this work draws on quite different scholarly traditions than those of media studies and sociology (i.e. it uses different methodologies, delimits objects of interest differently), we shall see how narrative studies also struggle with grasping the ambivalent nature of what digital communication platforms are in the midst of doing to human interaction.

1.3   Stories on Social Media The notions of ‘narrative’ and ‘story’ come with long and contested histories in diverse disciplinary traditions. A detailed discussion of the terminological and conceptual differences between ‘narrative’ and ‘story’ is beyond the scope of this book, but it is useful to note that in our discussion we will employ the term ‘narrative’ to refer to the formal object of inquiry in fields such as narratology and narrative analysis, while we will employ the term ‘story/stories’ to refer to everyday life narrative practices, including our material. In terms of widely agreed upon definitions of narrative, from within narratology, we take as our point of departure the designation of narrative as ‘the semiotic articulation of linear temporal sequence’ (Walsh 2018, 12). The close links of narrative with temporality is something that most studies converge on, but further to understandings of narrative as a text-type or a particular form of content are its conceptualizations as ‘a basic cognitive mode of sensemaking that creates meaningful form with a specific temporal logic’ (19). Tied to narrative as a basic mode of thinking are a string of effects or features. Because narrative ‘imposes’ its order on phenomena from ‘a specific spatial and temporal point’ (19), narrative thinking is seen as ‘perspectival’ and ‘evaluative’. As powerful as they may be in turning mere happenings into meaningful series of events, narratives are always angles on the world and they always leave something out—they rest ‘upon unexamined assumptions’ (23). This implicit character of narrative sensemaking is what gives it its reflexiveness. Narrative is, from this point of view, never complete and so the sense that it produces is always temporary and up for grabs, inviting continuous tellings and retellings.

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Any current discussion of narrative needs in our view to acknowledge the fact that the landscape of narrative studies, both within discourse analysis and sociolinguistics and within classical and postclassical narratology, has changed radically since the turn of the millennium. In what follows, we highlight key-insights on the nexus of narrative and social media in each subfield, beginning with narrative analysis and sociolinguistics. During the last 20 years, the field of narrative analysis has undergone profound developments, including a rethinking of the mainstay ways of defining, exploring and studying stories, in particular the role of the teller, story-ownership and the personal experiences story; time and space/place; tellability (the point and worthiness of a story); and, finally, the place of stories themselves in the contemporary world (for details, see De Fina and Georgakopoulou 2012). Specifically, the teller as a sole entity, in control and in possession of their story, has given way to contextual approaches that view stories as co-constructed and negotiable accounts (e.g. Ochs and Capps 2002). In a similar vein, the organization of a story, including its tellability, are nowadays viewed as situated and emergent in acts of communication, rather than as inherent to a particular subject matter or story topic and point. In turn, the tellers’ identities have been increasingly viewed as intricately connected with local purposes and practices of which a storytelling event becomes an integral part, and with participation roles pertinent to them. In particular, the shift to interactional approaches to identities or, as often called, identities-in-interaction within discourse studies and sociolinguistics has had a big influence on discourse approaches to narrative. These stress the multiplicity, fragmentation, context-­specificity and performativity of storytelling practices (see De Fina and Georgakopoulou 2012, Chap. 6). It is symptomatic of this shift that the term ‘stories’, with its emphasis on the multiplicity of actual instances of telling in everyday life, seems to have displaced the term ‘narrative’ in sociolinguistic studies. This rethinking of narrative has partly been the result of the increasing resonance of contextual, practice-based approaches to language and discourse and partly been necessitated and precipitated by major socio-­ cultural changes, including mobility, globalization and, as we will show below, social media communication. One paradigm that has been instrumental in opening up the lens of narrative analysis to what traditionally has been seen as atypical stories, as well as to the multiplicity of types of stories in everyday life, has been that of small stories research. The notion of smallness encapsulates the fleetingness of stories in interactional moments,

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their embeddedness in local contexts and the analyst’s attentiveness to the emergence of plots in the microcosm of everyday life experience (Bamberg 2006; Georgakopoulou 2006, 2007). Since its inception, empirical work has added nuance to the general descriptor of small stories, bringing to the fore specific genres of small stories that occur in specific contexts and that ought to be included in the narrative analytic lens (for details, see Georgakopoulou 2015a, 2019). This work has uncovered different types of social organization and relations that warrant or prohibit small stories, from friendship groups to social media apps, deliberation focus groups and professional organizations (Juzwik and Ives 2010; Page 2012; Sprain and Hughes 2015; Watson 2007). In recent work, Georgakopoulou (2013a, 2015a) has argued that small stories research prefigured the current situation of the proliferation of stories that fit the definition of ‘small stories’ on social media. Small stories research is thus well placed to ‘offer a conceptual apparatus for the study of new/social media practices that facilitate the circulation not just of personal stories, but of public and “news” stories too’ (Georgakopoulou 2013a, 20). One way in which to explore the dialectic between stories and media affordances is by contextualizing stories within the built-in logic and economy of breaking news in many social networking sites (Georgakopoulou 2013b). This is linked with the algorithmically shaped preference for recency of posts and sharing live. Georgakopoulou’s contention has been that this logic encourages the sharing of everyday life as stories, sharing-life-in-the-moment. Tied to the economy of breaking news is the notion of ‘narrative stancetaking’. The brevity and live-sharing affordances are conducive to announcements of stories (breaking news) as opposed to full tellings. Conventionalized story-framing devices (e.g. reference to time, place, characters) are used to tell a condensed story or to suggest that there is a story in the making (Georgakopoulou 2017). Narrativity can therefore be understood as an emergent property, a process of becoming a story through engagement. This has implications for how tellers are presented and for how their posts are engaged with. Running parallel to, yet mostly separated from, these developments in sociolinguistic approaches to narrative, the field of what was once referred to as narratology has since the early noughties evolved into several so-­ called postclassical narratologies (Herman 1999; Alber and Fludernik 2010). This involves a shift away from the text- and structure-based heritage from French structuralism, including its tendency to focus on fictional, literary narratives. Postclassical narratologies have instead turned

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their attention to contexts and materialities: cognition, ideology, rhetoric and media, with the latter two being most relevant to our aims in this book. From being a pursuit of studying either fictional narratives (Booth 1991; Phelan 1996) or narratives in rhetorical discourse (Fisher 1987), the interest in the rhetoric of narrative has been reinvigorated along two paths: Richard Walsh and others have shown how fictionality, far from being a turning away from the real world, restricted to certain genres, is a serious move in the real world that may appear in any text-type (Iversen and Nielsen 2017; Nielsen et al. 2015; Walsh 2007). Work on how rhetorical discourse uses narratives as means toward certain ends have focused on how storytelling motivate processes of identification and user motivation. Studies have shown how personal narratives can be made to serve specific rhetorical purposes (Anderson 2007; Andrews 2014; Iversen 2014, 2017; Iversen and Pers 2020; Shuman 2005). Recently, interest has been directed at the ‘curation’ of stories in various public domains (Fernandes 2017) and in the ability of certain types of stories to enter massive circulation (Mäkelä 2018). The interest of postclassical narratology in media was initially spearheaded by Marie-Laure Ryan who in 2004 edited Narrative Across Media. In this collection, Herman (2004) suggested the term transmedial narratology. The approach set out to counter media-blindness in the study of narrative by navigating between, on the one hand, the misconception that narrative is a language-based speech act rather than a multi-modal semiotic activity and, on the other hand, the misconception that different media are unable to tell the same story (Ryan 2006). Stories can be told in and across many different media, even as different media come with different narrative capabilities: ‘when it comes to narrative abilities, media are not equally gifted; some are born storytellers, others suffer from serious handicaps’ (4). Under the heading of transmedial narratology, three different avenues have opened up. One leads to insight into the storytelling abilities of specific media, most notably visual media, such as film (Kuhn 2013), television (TV) series (Mittell 2015), comics (Kukkonen 2013) and interactive media, such as computer games. Another is based on a narrower interest in ‘phenomena that manifest themselves across media’ (Thon 2016, 11), while a third leads to insights into stories that create ‘a storyworld through multiple documents belonging to various media’ (Ryan 2013, 361). While acutely aware of formal intricacies and complexities of narrative structures, transmedial narratology has, by and large, remained focused on fictional narratives. While heavily invested in

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understanding media-specific affordances, it has yet to systematically engage with social media platforms. An exception to this, and an interesting take on a narrow understanding of transmedial narratology, has been suggested by Mäkelä in her ‘literary-narratological analysis of non-literary material’ (2019, 160). By using the concepts of experientiality, simultaneity and tellability as transmedial concepts, she shows how self-storying on Facebook also has important aesthetic dimensions. ‘New’ Types of Stories, ‘New’ Types of Telling? Drawing on the above latest trends within the study of narrative, the studies that have explored stories on social media have brought to the fore distinctive genres of stories and salient ways of storytelling. Such studies converge on the importance of communicating recency of experience that leads to the frequency of breaking news stories (Dayter 2015; Georgakopoulou 2013b; Page 2012; West 2013). In addition, they have explored the fragmentation, multi-authorship and co-construction of stories in close connection with participation roles, practices of storytelling on the go (Georgakopoulou 2017) and processes of distribution that different platforms afford (e.g. Perrino 2017; Giaxoglou 2015; Marques and Michèle 2017; Vásquez 2017). At the same time, a contextually sensitive approach followed by such studies has also shed light on issues of variation of storytelling styles and genres, according to the exigencies of different environments, regarding, for instance, the use of Facebook for remembering and nostalgia (Georgalou 2015), the development of more continuous stories on Twitter through small stories (Dayter 2015), the tendency to have single tellership and linearity in some environments more than others (Page 2012) and so on. This strand of inquiry has also grappled with issues of methodology and analysis posed by social media communication, in particular the role of multi-semioticity and the ways in which it can be taken into account in the study of stories, given that traditional modes of analysis have been geared to focusing on language and text as the prime semiotic modality of stories (see Page 2018). Similarly, studies have discussed the difficulties of transferring sequential, interactional models of analysis, as well as ethnographic ways of data collection, alongside showing how emerging approaches such as online conversation analysis and discourse-centred online ethnography can be fruitfully drawn upon for the study of stories online (e.g. Georgakopoulou 2015a, 2017; papers in De Fina and Perrino 2017).

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Storytelling Participation Between Agency and Media Affordances So far, we have focused on the development of new concepts and conceptualizations by narrative analysts interested in the nexus of storytelling and social media. There is still much scope in this strand of inquiry for fully addressing, methodologically and analytically, the role of the technological materiality and algorithmic and socio-technical design of social media platforms in the telling of stories. Put in Papacharissi’s terms, we still need to explore ‘how the stories people share, in performing the networked self, are restricted, enhanced, and adorned by the affordances of these platforms’ (2018, 4). Most early debates about digital storytelling3 highlighted its positive, empowering potential, especially in terms of giving a voice and opportunities to ordinary people for sharing their experiences, in particular, disruptive experiences such as illness. The ‘Digital Storytelling movement’, as Clark et al. refer to it (Clark et al. 2014, 923), believes that ‘conversational media’ (Lambert 2006, 17) can address ‘lack of recognition’ and ‘engage us in listening to each other’s stories with respect’ (xx–xxi). But beneath this celebratory rhetoric lies important attention to what Clark and others refer to as the mediation of digital storytelling: the insight that the formats of digital storytelling are not simply containers into which existing narrative material may be poured but that these new genres and the practices they entice are dialectically linked with their users and contexts. More recent studies of stories online with similar preoccupations about their participatory potential and the formation of collective stories and collectivities through stories engage with the distribution and multi-­ participation affordances of social media. A case in point is Papacharissi’s work which zooms in on the particular forms of information production and information circulation that Twitter facilitates and how those are tied to storytelling. Using computational discourse analysis to map traffic around selected viral hashtags, a key-finding has been that Twitter produces ‘affective news streams’ (Papacharissi and Oliveira 2012, 14) of information that blends ‘opinion, fact, and emotion into expressions uttered in anticipation of events that had not yet attained recognition through mainstream media’ (14). In a series of publications, Papacharissi and others build on these findings on what a trending, politically motivated hashtag in Twitter does by elaborating on boyd’s idea of a networked public by suggesting the term ‘affective publics’ (Papacharissi

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2014, 2015; Papacharissi and Blasiola 2017): ‘the form of content streams […] is affective in nature […] and these streams serve to discursively call in to being public formations, that I refer to as affective publics. They serve as storytelling structures that sustain a modality of engagement that is primarily affective’ (Papacharissi 2015, 4; cf. Giaxoglou 2015). A clear strength of this work lies in the innovative, affect-sensitive analysis and interpretations of the distinctiveness of the type of interactive, simultaneous communication and sharing that the social media infrastructure, particularly the hashtag, facilitates. Such an emphasis on how participation and distribution affordances affect the textual properties of stories and the meaning-making through them, as they are distributed across media platforms and across media, is also taken up in discourse analytic and sociolinguistic studies of storytelling (e.g. De Fina and Gore 2017). They have shown, for example, how a story’s distribution across sites routinely involves creative reworkings of its plot by different audiences (e.g. Georgakopoulou 2014, 2015b) and how such recontextualizations bring about different meaning-making potentials and construct different evaluative stances (e.g. Perrino 2017; Blommaert and Varis 2015). Similarly, they have begun to document the specific ways in which certain participation roles give rise to the collectivization of stories (e.g. Giaxoglou 2017). Despite a lack of an explicit comparative focus between conversational, face-to-face stories and stories on social media, one productive result of such an inquiry is the gradual emergence of a thick description of how participation in stories on social media is reconfigured. Situating our approach in relation to this quite diverse body of existing work on narratives and social media, the main intention is to further develop two tendencies that we find important in order to understand the phenomena under scrutiny in this book. First, we want to latch on to the emerging recognition in some of this research that understanding platformed narration requires not just fine-tunings of existing theories about narration but also a substantial rethinking of key-concepts, such as interaction, tellership and tellability and, more broadly, the idea of living narratives. Second, by focusing on the nexus of metrics with stories as part of examining the affordances of platforms, we hope to avoid the pitfalls of technological determinism of either the utopian or dystopian variety.

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1.4   Quantified Storytelling: Our Approach As shown, metrics and stories on social media have been researched separately in different disciplines and traditions, but the links of quantification with stories have not been explored sufficiently in either storytelling research or in social media studies. This is despite the fact that social media platforms have the complex intertwinement of storytelling and metricization processes as a core feature. In this book, we seek to address this gap for exploring storytelling as quantified activities on social media and by empirically documenting the changes that story genres and practices are undergoing and the ways in which they are shaped by and adapted to social media ecologies. The interdisciplinary ambition of this book is therefore to contribute to storytelling research with an increased awareness of social media and platforms and to social media studies with sustained and updated approaches to storytelling. Focusing on numbers or quantification to understand narratives on social media might at first come across as an approach that limits the analytical focus too drastically. Our point is of course not that quantification is the only valid framework by analysing this type of material, but rather that focusing on numbers and metricization is a constructive narrowing down of focus. Beginning with quantification as an overall lens allows us to ask different and more fundamental questions about how storytelling develops within the ‘measurement regime’ of social media, instead of taking part in the often-unsatisfying task of trying to transfer concepts developed for understanding different types of storytelling onto the study of social media. Questions and Methodology The book employs a mixed method approach that combines qualitative methods such as close, narrative analytic readings of case studies and coding with quantitative methods of corpus analysis. More specifically, Chap. 2 is based on the coding of 1069 Instagram posts made by three female cancer patients in order to analyse the metricized narrative dynamics over time on the profiles. The number of Likes, comments and views of the singular posts and recordings were also registered to, for example, create lists of the most commented-upon and most Liked posts on each of the profiles. The object of study of Chap. 3 is the subreddit ‘The_Donald’ (TD) on www.reddit.com. Here, we attempt a close reading of the life and

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circulation of one exemplary and highly mobilizing post (including comments): ‘Trump: As president, I would prosecute Clinton’, which was posted on February 23, 2016. Chapter 4 uses a corpus-assisted discourse analytic method to analyse media app companies’ briefs and blog posts, documents that outline technical specifications of new features and media reports in the time interval between May 9, 2012, and January 30, 2018. This was done so as to make sense of the design perspective on metricization related to the introduction and review of Snapchat Stories (2014) and Instagram Stories (2016). The corpus is supplemented by a case study of the female Influencer Lele Pons, an American-Venezuelan Instagram and YouTube celebrity with the most watched Stories, according to Instagram’s released figures. This data collection has involved mining stories (as multi-­ modal data with their metadata) in an automatic collection period of 20 days in January 2019, and the data amount to 406 Stories made by Lele Pons. By combining single case studies, manual coding of posts and computational methods for analysing corpora, we aim to create knowledge about quantified storytelling on both micro and macro levels by mixing in-depth explorations of textual examples with the analysis of larger discursive patterns. Despite differences in the amount of empirical material and analytical approaches in the three chapters, they all share a concern with understanding the cultural and technological implications of quantified storytelling in a tension between (1) agentive practices of users and collectives on the one hand and (2) platformed affordances on the other. In terms of platforms, we include a substantial amount of material (e.g. posts, comments and more ephemeral stories) from Instagram, Snapchat and reddit and supplementary examples from Facebook. We furthermore engage with quantified communication processes involving ordinary users during existential disruption and political movements, as well as platform designers and professionalized Influencers. In that way, our discussion brings in insights into quantified storytelling across a variety of platforms and user groups. Collection of empirical material that refers to specific persons is based on informed consent, and comments made by ordinary users are anonymized. Ethical considerations linked to exploring the storytelling practices of cancer patients are dealt with more in depth in Chap. 2. The collection, storing and removal of digital material will all be handled according to the General Data Protection Regulation (GDPR).

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A Heuristic Typology of (In)Visible Metrics As a tool for analytically approaching the three research questions, we expand Bucher’s distinction between visible metrics available to all interface users (e.g. the Like score) and the more opaque metricization involved in algorithmic measurement of user behaviour on social media (Bucher 2018, 11–12) with a third level of metrics, inspired by the literature on self-tracking and ‘the quantified self’, as described earlier in this chapter (see also Stage 2019). Specifically, we distinguish between three types of metrics: 1. Content metrics: Numbers, measurements and quantities can be a part of what posts on social media are about. Many stories on platforms revolve around and make reference to quantifiable phenomena, such as self-measurements, quantifiable goals, countdowns, quantified engagement with previous spreadable posts and so on. Content metrics are, in other words, quantification practices that users can choose to include in the posts they share on social media. 2. Interface metrics: Social media interfaces are permeated by in-built instruments for measuring and keeping track of all sorts of user activity: for example, scores of Likes, views, shares, comments and so on. As we will show, interface metrics are not peripheral or supplementary to the storytelling practices unfolding on the platforms but ingrained in these practices. 3. Algorithmic metrics: The back end of most platforms comprises largely opaque algorithmic processes, affecting, among others, visibility, moderation, spread and sequencing of storied content. These processes measure users’ behavioural patterns according to a range of invisible personalizing metrics, while at the same time affecting the future content that users see, but also the mediatized choices that users, institutions and organizations make, in order to perform well on social media. The distinction between these three interrelated yet analytically separable levels makes it possible to scrutinize different aspects of how storytelling and quantification intermingle on social media. When we refer to ‘quantified storytelling’ as the core interest in this book, this implies storytelling across all three levels: stories about/with numbers using content metrics, numbered story responses relying mainly on interface metrics and the algorithmic shaping of stories and their circulation.

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A crucial point in relation to the analytical potential of these metrics is that they are visible and invisible on social media in different ways, at the same time as distributing what becomes visible and invisible on social media. They are, in other words, embedded in and contribute to complex cultural and technological systems of (in)visibility (Bucher 2017; Stage 2017). Intuitively, many would probably assert that content metrics and interface metrics are visible, while algorithmic measurements are invisible. While there is some truth to this claim, we also show with our case studies that the visibility of a singular metric is a highly distributed and tiered quality defined and developed through the intertwinement of the different types of metric. Content metrics on, for example, Facebook are of course immediately visible to the eye in posts, but only to the singular users who have engaged with previous content (e.g. by liking it) in ways that algorithmic measurements identify as relevant for making the new post appear in the personalized feed. The visibility of interface metrics is also distributed differently. Instagram Influencers with many followers, for example, have access to more in-built metrics than ordinary users (cf. Chap. 4), and as mentioned, experiments are currently being made on discriminating between profile owners’ and followers’ access to the Like score on Instagram. And algorithmic measurements are of course mainly invisible, but also become indirectly visible to users, for example, through the personalization of news feeds, the sudden occurrence of targeted ads on profiles revealing of algorithms at work or indeed tech companies’ own revelations of factors that weigh in their algorithmic calculations. Key-Insights: Metricized Formats, Engagement and Power The three analytical chapters in various ways explore quantified storytelling across: (1) the how of this narrative practice, (2) the user engagement and circulation processes linked to metricized storytelling and (3) the larger cultural discourses, power dynamics and identity positions (re)produced by quantified storytelling. Concerning the communicative how of stories, quantification can be deployed to document ordinary life through small stories (e.g. in posts sharing visualizations from health and running apps). As we will show, numbers can also take on a special narrative role when tellers are faced with existential disruption, such as serious illness (cf. Chap. 2). Here, counting and tracking stages towards a desired goal—what we call teleological counting—become an affective, therapeutic narrative technique for

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keeping the teller on track, a resource for adhering to cultural master plots and for engaging audiences in supportive processes of overcoming existential suffering. Quantified storytelling through counting stages is also a way of adapting narratives of disruption to the affordances and value chains of social media platforms that privilege ongoing, brief, emblematic and affectively intense—often happy or hopeful—postings and interactions. The metricizing teller can, however, be challenged by either incurability or actually reaching the goal of a self-tracking process and thus face the relational tellability crisis of having to redefine what is worth telling from the perspective of the followers. The affordances of social media as numbering ecologies encourage users to immediately share ongoing, present moments of everyday life, but the constant scoring of what is shared also continuously valuates the shared post by showing how it is responded to. As we will show, peaks related to specific posts do not only document the achieved circulatory value of what is shared but can also be turned into key-content for future posts—for example, in chains of memetic rescriptings—that narrate how previous posts were quantified. These stories about numbers are termed reflexive quantified storytelling (cf. Chap. 3). In that way, we distinguish between numbers in social media stories, designating a story that involves some element of quantification, and numbers as social media stories, which refers to the narrative act of using social media quantifications as the very stuff of a posted story. Quantification plays a crucial role not only for formats and ways of telling, but also for the distribution, ordering, ranking and amplification of stories, and for the mobilization through stories. Processes of ranking and ordering stories on platforms can be co-constructed in more or less transparent ways (cf. reddit vs. Facebook). But platforms also distribute knowledge about how content has been circulated to users in different ways—for example, by giving Instagram Influencers access to what we call most valuable player metrics (MVP metrics) that allow them to track and document the impact of their shared content. In this respect, the constitution of the Influencer self is also enacted through its capacity to reach popularity targets that give access to otherwise hidden measurements, able to assist Influencers in optimizing the future traction of their posts and stories. Metrics are, however, not only deployed to measure and performatively amplify circulation in relation to individuals. Dealing with and manipulating metrics can also become a crucial tool for collectives and social movements—for example, on reddit—trying to break into the more visible

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mainstream. Amplifying scores of posts is thus used as a strategy for promoting and mobilizing political counterpublics, through processes of heated, intense and sometimes toxic bettering of interface metrics. Audience engagement and interaction thus become quantifiable: you engage by pushing social buttons, adding to comment scores or recirculating quantified story elements. This shift, we argue, inherently changes the logic of political mobilization towards more brief and connective practices, as well as personalized uses of templates and action frames, with the overall goal of manufacturing visibility and creating a sense of a collective push for change. A broader focus of the book is how these overlapping quantification processes position tellers, as individuals and groups, in different ways and how they encourage and discourage, make available and visible or, equally, silence particular narrative practices, discourses and affective economies. This is closely connected to an awareness of how the affordances of platforms organize social life and valorize user activities. To this effect, we use the concept of directive so as to zoom in on particular aspects of the broader notion of affordances that ‘refers to the range of functions and constraints that an object provides for, and places upon, structurally situated subjects’ (Davis and Chouinard 2016, 241). The analytical implications of the concept of affordances can, according to Davis and Chouinard (2016), be specified, by focusing on how, for example, technological objects simultaneously ‘request’, ‘demand’, ‘encourage’, ‘discourage’, ‘refuse’ and ‘allow’ particular forms of action (cf. Chap. 4). ‘Directives’, as explored in this book, are primarily linked to the requesting and encouraging aspects of platform affordances by describing how platforms seek to push users towards particular communicative and interactional practices by means of quantified processes. Our study of the design of Stories as a feature on Snapchat and Instagram brings to the fore three such directives: life-sharing-in-the-moment, audience engagement as quantified viewing and tellers’ construction of authentic selves (cf. Chap. 4). On social media, what can be measured counts (Porter 1996, 43) and more is better (Bucher 2018, 12). This directs users towards practices that can be scored (e.g. in views or Likes) but also towards those that are scored higher (e.g. emblematic events rather than tedious ones). But what travels on social media is not only determined by technology but rather also constituted through complex assemblages of users, technologies and cultural aspects that (pre)position and valorize particular sharing practices, digital skills, subjectivities, bodies, approaches to disruption, privacy and

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political interaction. Through these filtering processes, particular plots, discourses and practices of exclusion and inclusion are (re)produced. These, as we show in our analyses, generally prioritize happiness over negativity, the brief over the long, the emblematic over the boring, the heated over the rational, the now (and the future) over the past, the appealing (or repulsive) over the affectively neutral, sharing over being private and attention (plus distraction) over detachment. As argued by Hacking, though, the need for measurement logically presupposes that social life is to some extent unpredictable, because measurements are focused on shaping the future, so as to make it more optimal than the past and the present, according to the standards of a specific measurement regime (Hacking 1990). This implies that an analysis of quantified storytelling should take into account both (1) how it feeds into the reproduction of problematic discourses and datafication/monetization processes on a variety of levels and (2) how metrics are not only behavioural cages but also complex agentive tools open to a variety of sometimes unpredictable, therapeutic, tweaking and protesting uses.

Notes 1. https://twitter.com/ReutersTech/status/966725621274632197 2. We follow Ed Finn’s definition of ‘algorithms’: ‘(T)he word algorithm frequently encompasses a range of computational processes including close surveillance of user behaviors, “big data” aggregation of the resulting information, analytics engines that combine multiple forms of statistical calculation to parse that data, and finally a set of human-facing actions, recommendations, and interfaces that generally reflect only a small part of the cultural processing going on behind the scenes’ (Finn 2017, 16). 3. The term ‘digital storytelling’ originates in what in 1998 became the Center for Digital Storytelling (since 2015 known as StoryCenter) at Berkeley, led by, among others, Joe Lambert.

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Georgakopoulou, Alexandra. 2006. Thinking Big with Small Stories in Narrative and Identity Analysis. Narrative – State of the Art. Special Issue of Narrative Inquiry 16: 129–137. ———. 2007. Small Stories, Interaction and Identities. Studies in Narrative 8. Amsterdam and Philadelphia: John Benjamins. ———. 2013a. Small Stories Research as a Framework for the Study of Social Media Practices: Narrative Stancetaking and Circulation in a Greek News Story. Sociolinguistica 27 (Special Issue): 19–36. ———. 2013b. Storytelling on the Go: Breaking News Stories as a Travelling Narrative Genre. In The Travelling Concepts of Narrative, ed. Matti Hyvarinen, Mari Hatavara, and Lars-Christer Hyden, 201–224. Amsterdam and Philadelphia: John Benjamins. ———. 2014. Small Stories Transposition & Social Media: A Micro-perspective on the ‘Greek Crisis’. Discourse & Society 25 (Special Issue): 519–539. ———. 2015a. Small Stories Research: Issues, Methods, Applications. In Handbook of Narrative Analysis, ed. Anna De Fina and Alexandra Georgakopoulou, 255–271. Malden, MA: Wiley-Blackwell. ———. 2015b. Sharing as Rescripting: Place Manipulations on YouTube Between Narrative and Social Media Affordances. Discourse, Context & Media 9: 64–72. https://doi.org/10.1016/j.dcm.2015.07.002. ———. 2017. Sharing the Moment as Small Stories: The Interplay Between Practices & Affordances in the Social Media-Curation of Lives. Storytelling in the Digital Age. Narrative Inquiry 27 (Special Issue): 311–333. ———. 2019. Designing Stories on Social Media: A Corpus-Assisted Critical Perspective on the Mismatches of Story-Curation. Linguistics and Education. https://doi.org/10.1016/j.linged.2019.05.003. Georgalou, Mariza. 2015. Small Stories of the Greek Crisis on Facebook. Social Media and Society. https://doi.org/10.1177/2056305115605859. Gerlitz, Carolin. 2016. What Counts? Reflections on the Multivalence of Social Media Data. Digital Culture and Society 2 (2): 19–38. Gerlitz, Carolin, and Anne Helmond. 2013. The Like Economy. New Media and Society 15 (8): 1348–1365. Gerlitz, Carolin, and Celia Lury. 2014. Social Media and Self-Evaluating Assemblages. Distinktion: Scandinavian Journal of Social Theory 15 (2): 174–188. Gerlitz, Carolin, and Bernhard Rieder. 2014. Techniques of Intersection - Metrics as Connectors and Separators in Twitter Research. Selected Papers of Internet Research 15: The 15th Annual Meeting of the Association of Internet Researchers, Daegu, Korea. Giaxoglou, Korina. 2015. ‘Everywhere I Go, You’re Going With Me’: Time and Space Deixis as Affective Positioning Resources in Shared Moments of Digital Mourning. Discourse, Context and Media 9: 55–63.

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———. 2017. Storying Leaks for Sharing: The Case of Leaking the “Moscovici draft” on Twitter. Discourse, Context & Media 19: 22–30. Hacking, Ian. 1990. The Taming of Chance. Cambridge: Cambridge University Press. Herman, David, ed. 1999. Narratologies: New Perspectives on Narrative Analysis. Columbus: Ohio State University Press. ———. 2004. Toward a Transmedial Narratology. In Narrative Across Media: The Languages of Storytelling, ed. Marie-Laure Ryan. Lincoln: University of Nebraska Press. Iversen, Stefan. 2014. Narratives in Rhetorical Discourse. In Handbook of Narratology, ed. Peter Hühn et al., 575–587. Göttingen: de Gruyter. ———. 2017. Narratives and Online Decorum: The Rhetoric of Mark Zuckerberg’s Personal Storytelling on Facebook. Style 51 (3): 374–390. Iversen, Stefan, and Henrik Skov Nielsen. 2017. Invention as Intervention in the Rhetoric of Barack Obama. Storyworlds 9 (1–2): 121–142. Iversen, Stefan, and Mikka Lene Pers. 2020. Interlocking Narratives: The Personal Story and the Masterplot in Political Rhetoric. In Exploring Fictionality: Conceptions, Test Cases, Discussions, ed. Maagaard et al. Odense: Odense University Press. Jenkins, Henry. 2006. Convergence Culture. New York: New York University Press. Jenner, Kylie. 2018. sooo does anyone else not open Snapchat anymore? Or is it just me... ugh this is so sad. 21 February, 10:50 PM. Tweet. Juzwik, Mary M., and Denise Ives. 2010. Small Stories as Resources for Performing Teacher Identity: Identity-in-Interaction in an Urban Language Arts Classroom. Narrative Inquiry 20 (1): 37–61. Kuhn, Markus. 2013. Filmnarratologie: ein erzähltheoretisches Analysemodell. In Berlin. Boston: De Gruyter. Kukkonen, Karin. 2013. Contemporary Comics Storytelling. Lincoln: University of Nebraska Press. Lagerkvist, Amanda. 2017. Existential Media: Toward a Theorization of Digital Thrownness. New Media and Society 19 (1): 96–110. ———. 2018. Numerical Being and Non-Being: Probing the Ethos of Quantification in Bereavement Online. In A Networked Self and Birth, Life, Death, ed. Zizi Papacharissi. New York: Routledge. Lambert, J. 2006. Digital Storytelling: Capturing Lives, Creating Community. 2nd ed. Berkeley, CA: Digital Diner Press. Lupton, Deborah. 2016. The Quantified Self. Cambridge: Polity. Mäkelä, Maria. 2018. Lessons from the Dangers of Narrative Project: Toward a Story-Critical Narratology. Tekstualia 1 (4): 175–186. ———. 2019. Literary Facebook Narratology: Experientiality, Simultaneity, Tellability. Partial Answers: Journal of Literature and the History of Ideas 17 (1): 159–182.

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Marques, Isabella Simões, and Koven Michèle. 2017. French Luso-descendants’ Diasporic Facebook Conarrations of Vacation Return Trips to Portugal. Narrative Inquiry 27: 286–310. Marres, Noortje. 2012. Material Participation. Basingstoke: Palgrave. ———. 2017. Digital Sociology. Cambridge: Polity. McCosker, Anthony. 2017. Data Literacies for the Postdemographic Social Media Self. First Monday 22 (10). Mittell, Jason. 2015. Complex TV: The Poetics of Contemporary Television Storytelling. New York: New York University Press. Neff, Gina, and Dawn Nafus. 2016. Self-tracking. Cambridge, MA: MIT Press. Nielsen, Henrik Skov, James Phelan, and Richard Walsh. 2015. Ten Theses About Fictionality. Narrative 23 (1): 61–73. Ochs, Elinor, and Lisa Capps. 2002. Living Narrative. Creating Lives in Everyday Storytelling. Cambridge: Harvard University Press. Page, Ruth. 2012. Stories and Social Media: Identities and Interaction. In New York. London: Routledge. ———. 2018. Narratives online. Shared Stories in Social Media. Pantzar, Mika, and Minna Ruckenstein. 2017. Living the Metrics: Self-tracking and Situated Objectivity. The Senses and Digital Health 3: 1–10. Papacharissi, Zizi. 2014. Affective Publics: Sentiment, Technology, and Politics. New York: Oxford University Press. ———. 2015. Affective Publics and Structures of Storytelling: Sentiment, Events and Mediality. Information, Communication & Society 19 (3): 307–324. ———, ed. 2018. A Networked Self and Platforms, Stories, Connections. Boca Raton, FL: Routledge. Papacharissi, Z., and Stacy Blasiola. 2017. Structures of Feeling, Storytelling, and Social Media: The Case of #Egypt. In Routledge Companion to Social Media and Politics, ed. Axel Bruns et al. London: Routledge. Papacharissi, Zizi, and Maria de Fatima Oliveira. 2012. Affective News and Networked Publics the Rhythms of News Storytelling on #Egypt. Journal of Communication 62 (2): 266–282. Perrino, Sabina. 2017. Recontextualizing Racialized Stories on YouTube. Narrative Inquiry 27: 261–285. Phelan, James. 1996. Narrative as Rhetoric: Technique, Audiences, Ethics, Ideology. Columbus, OH: Ohio State University Press. Porter, Theodore M. 1996. Trust in Numbers. The Pursuit of Objectivity in Science and Public Life. Princeton, Princeton University Press. Power, Michael. 2004. Counting, Control and Calculation: Reflections on Measuring and Management. Human Relations 57 (6): 765–783. Rogers, Richard. 2018. Otherwise Engaged: Social Media from Vanity Metrics to Critical Analytics. International Journal of Communication 12: 450–472.

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Ryan, Marie-Laure. 2004. Introduction. In Narrative Across Media: The Languages of Storytelling, ed. Marie-Laure Ryan, 1–40. Lincoln: University of Nebraska Press. ———. 2006. Avatars of Story. Minneapolis: University of Minnesota Press. ———. 2013. Transmedial Storytelling and Transfictionality. Poetics Today 34 (3): 361–388. Shuman, Amy. 2005. Other People’s Stories. Urbana and Chicago: University of Illinois Press. Sprain, Leah, and Jessica M.F.  Hughes. 2015. A New Perspective on Stories in Public Deliberation: Analyzing Small Stories in Discussions About Immigration. Text & Talk 35 (4): 531–551. Staeheli, Urs. 2012. Listing the Global. Distinktion: Scandinavian Journal of Social Theory 13 (3): 233–246. Stage, C. 2017. Networked Cancer. Affect, Narrative and Measurement. Basingstoke: Palgrave. ———. 2019. Affective Measures: Self-measurement and Gridding in Female Cancer Patients’ Storytelling Practices on Instagram. Distinktion 20 (1): 77–100. Thon, Jan-Noël. 2016. Transmedial Narratology and Contemporary Media Culture. Lincoln: University of Nebraska Press. van Dijck, José. 2013. The Culture of Connectivity. New  York: Oxford University Press. van Dijck, José, Thomas Poell, and Thomas de Waal. 2018. The Platform Society. Public Values in a Connective World. Oxford University Press: New York. Vásquez, Camila. 2017. ‘My Life has Changed Forever!’ Narrative Identities in Parodies of Amazon Reviews. Narrative Inquiry 27: 217–234. Walsh, Richard. 2007. The Rhetoric of Fictionality. Columbus: Ohio State University Press. ———. 2018. Narrative Theory for Complexity Scientists. In Narrating Complexity, ed. Walsh and Stepney. Cham, Switzerland: Springer. Watson, Cate. 2007. Small Stories, Positioning Analysis, and the Doing of Professional Identities in Learning to Teach. Narrative Inquiry 17 (2): 371–389. West, L.E. 2013. Facebook Sharing: A Sociolinguistic Analysis of Computer-­ Mediated Storytelling. Discourse, Context & Media 2: 1–13.

CHAPTER 2

Measuring and Narrating the Disrupted Self on Instagram

2.1   Introduction This chapter will pay specific attention to what we have called ‘content metrics’, defined as user-driven and visible acts of measurement and counting shared through text and images on social media platforms. We will explore the analytical potential of content metrics by focusing on examples of cancer storytelling on Instagram. Preceding Chap. 3 on storytelling and its links with quantified mobilization and preceding the focus of Chap. 4 on the increasingly professionalized attention economy of metrics in stories as designed features, Chap. 2 explores ordinary users’ practices of personal storytelling. More specifically, it investigates how individuals deploy quantification and counting in their social media postings in order to tell stories about how the everyday self transforms, develops and affectively relates to itself during existential disruption. Although the topic of illness, and more specifically cancer, is highly culturally contextualized and linked to specific narrative master plots and metaphors, the type of quantified cancer storytelling dealt with in this chapter is intended as relevant for studies of other types of quantified storytelling linked to disruption, emergency and sudden or desired life change: for example, related to other illnesses, injury, weight loss, death and commemoration, rehabilitation, pregnancy, unemployment, divorce and so on. The chapter will deal with various examples of quantified storytelling as part of an ongoing medical treatment during which a patient attempts to ‘move through’ illness in favour of a cure. Other counting practices can, © The Author(s) 2020 A. Georgakopoulou et al., Quantified Storytelling, https://doi.org/10.1007/978-3-030-48074-5_2

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however, also be identified in relation to cancer storytelling on social media. When serious illnesses are incurable, the practice of counting stages towards a telos, which we will call ‘teleological counting’, is often replaced by a different kind of ‘cumulative counting’, where achievements in the past or in the here and now instead become central (Stage 2017). The English blogger Stephen Sutton (1994–2014) is an example of how illness stories can break with teleological counting in favour of cumulative counting and storytelling after the hope of being cured is no longer realistic. Sutton was born in December 1994 in the United Kingdom and lived an ordinary life until September 6, 2010, when he was first diagnosed with colorectal cancer. On December 7, 2012, after a series of operations and chemotherapy treatments, Sutton was told that the doctors could not cure his disease. On January 13, 2013, Sutton established the Facebook page Stephen’s Story. Here, Sutton shared his very personal and intimate struggle against cancer but also crowdfunded approximately GBP 5 million for the Teenage Cancer Trust in the United Kingdom through more than 182,000 donations on the crowdfunding service JustGiving. In a video made by Sutton, When life gives you cancer (2014), he very clearly addresses how incurability has caused a change in measurement regimes, as he is no longer measuring life in terms of time, but in terms of achievement: I do not know how long I have got left to live. But one of the reasons for that is that I have not asked. And that is because I have entered a point in measuring life where I am not measuring life in terms of time anymore. I would rather measure it in terms of what I actually achieve. I would rather measure it in terms of making a difference, which I think is a much more valid and pragmatic measure (05.54.00).1

This movement from measurement of temporal progression to accumulation first and foremost signals that the future as a sphere of action is closed and that personal agency can only be pragmatically maintained in the near-present. This also poses a change in narrative logic as the numbers are not used to narrate temporal movement, but rather to produce a sense of existing ‘enormity’ and abundance that positions the self as extraordinary. In that way, counting is all about making the value of the teller’s achievements reportable or visible in the present and to shape the teller’s future public heritage. The role of metrics and counting as a continuous resource for constructing the identity of a patient through stories and, more specifically, as

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a means of projecting a cured self onto the future has not been addressed in depth in existing research on illness storytelling. Instead, studies have primarily been focused on the disruptive advent of illness and the reparative narrative work it affords. Studying the life-writing of individuals with serious illness is closely connected to the concept of ‘illness narrative’, which, at least since the 1990s, has influenced various disciplines such as medical anthropology (Mattingly 1998; Kleinman 1988), sociology and social work (Frank 1995; Hydén 1997; Williams 2000; Hardey 2002), literary studies and language (Jurecic 2012; Page 2012; Couser 2016) and health, medicine and medical humanities (Skott 2002; Shapiro et al. 2009; Charon 2006; Hawkins 1999). The core interest of these scholars has been to understand how people facing illness use and express themselves through narratives and to articulate the individual and embodied experience of illness as a counterpart to a purely medical approach to the body. A widespread view in the illness narrative literature is that narratives serve to order and tame the drama and chaos of illness, which creates a ‘biographical disruption’ (Bury 1982, 167) and a ‘painful disintegration of both self and world in everyday life’ (Skott 2002, 231). Narration is thus often understood as an act of ‘making sense’ of this senseless event and as reconstructing some element of structure, selfhood and capacity to act by, for instance, attributing certain metaphors or narrative causalities to the process (for example, illness as travel/journey, battle, war, rebirth (Hawkins 1999; Henriksen 2014; Stacey 1997; Sontag 1991)). As part of this tradition, Arthur Frank has offered a particularly influential distinction between three types (or master plots) of illness narrative: 1. The ‘restitution story’, where illness occurs and is treated in order to restore health with the positive help of the health care system. In this sense, narrative ‘represents the triumphant optimism of medical science’ (Frank 1998, 201). 2. The ‘chaos story’, where illness cannot be cured or treated successfully and thus creates a process of fragmentation and social disintegration. ‘If our culture loves the restitution narrative that any illness can be cured, it fears the chaos narrative that, with illness, troubles multiply’ (Frank 1998, 202). 3. The ‘quest story’, where illness is narrated as ‘a condition from which something can be learned (though not in a didactic sense) and this learning can be passed on to others’ (Frank 1998, 203).

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Through this quest the illness transforms the narrator in a positive way through new insights and existential revelations. (Semi)-public narrations of cancer on social media platforms—such as blogs, Facebook, Instagram and YouTube (Kaplan and Haenlein 2010; Klastrup 2016)—have attracted academic interest over the last decade (Pitts 2004; Coll-Planas and Visa 2016; Nesby and Salamonsen 2016; Heilferty 2018; Andersson 2017; Orgad 2005). However, analytical approaches to this type of narrative material are still to a large degree modelled on the aforementioned textualist typologies and definitions primarily developed in literary studies and aimed at understanding larger and coherent book-based illness narratives (Frank 1995; Hawkins 1999; Jurecic 2012). Personal accounts of cancer on social media are thus simply often treated as if they were books—that is, as solidified textual entities characterized by a particular narrative structuration of past events and with a single dominant narrator communicating his or her individual story to an audience. Research on illness narratives on social media that explicitly challenge this formalist or textualist model (Bamberg 2016) is, in other words, rare. When the particular affordances (Davis and Chouinard 2016) of social media in terms of narrating illness are actually acknowledged, a change in temporal tellership (from retrospective to present narration) is most often stressed as crucial (Tembeck 2017; Arduser 2017; Bolaki 2016; Page 2012; Orgad 2005). Neglecting the affordances of social media has a range of other problematic consequences than overlooking this shift in temporal organization: for example, the ‘living’ (Ochs and Capps 2002), interactional and metricized aspects of narrating cancer on social media are downplayed—or at least not sufficiently integrated into the methodologies developed to approach this type of storytelling activity.

2.2   The Quantification of Illness Narratives on Instagram Cancer has its own particular affective economy (Ahmed 2004) as the most feared disease in a Western context followed by Alzheimer’s and heart disease (Alzheimer Europe 2011). In the twentieth century, an increasing number of patients shared their version of living with, and often fighting against, this culturally dreaded disease in books. This public

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personalization of illness has been conditioned by overlapping developments, such as better and successful treatment (creating the opportunity to actually narrate one’s story), an increased professionalization and centralization of health care (creating a demand to be heard as a person with a story), technological changes and decreasing costs concerning print technologies (e.g. the paperback revolution in the 1930s), but also by the rise of a more politicized notion of the patient (e.g. through various patient movements like the women’s health movement) (Jurecic 2012; Rose 2006). The rise of social media has further supported this tendency to share personal accounts of cancer due to easy-to-use platforms. These media technological changes also imply that dynamic and ongoing measurements take on a more prevalent role in this type of storytelling; for example, since both the production of and the response to stories are continually datafied by social media platforms, this allows these platforms to compare and monetize user behaviour and personalize future content (McCosker 2017; Dijck et al. 2018; Finn 2017). An important point is that stories of cancer are not only quantified from the outside, that is, through processes of visible social scoring or invisible datafication built into the platforms; they are also quantified from the inside, since storytellers take up processes of self-measurement as a more integrated part of the day-to-day accounting (Humphreys 2018) of illness on social media. The term ‘self-­ measurement’ refers both to measurements initiated by the poster (e.g. by posting a picture of hair measurement) and processes of measurement initiated by others (e.g. the medical system) that are articulated or visualized by the patient on their profile (Stage 2019a). Since many patients now have the ability to track and interpret cancer experiences as they develop, on social media, it has become a more widespread practice to measure and compare phases and bodily changes as an integral part of sharing these illness stories. Furthermore, self-­measurement seems to fit the narrative affordances of, for example, Instagram—privileging brevity, visuality and selfies—particularly well (Georgakopoulou 2016b; Marwick 2015; Lobinger 2016; Ibrahim 2015). Simultaneously, the platforms themselves constantly measure social responses through scores of views, Likes (or other reactions) and comments and thus also motivate affective responses to these scores, which are sometimes shared in future posts or, if sufficiently large or explosive, taken up by traditional media, for example, as stories about virality or crowdfunding achievements (Stage 2017) (see also Chap. 3 on ‘reflexive storytelling’). Tracking cancer

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processes as they develop, through self-measurement, and responding to scores of responses made by other users have, in other words, become keydimensions of telling a cancer story on social media as new ‘numbering ecologies’ (Day et  al. 2014; Neff and Nafus 2016; Lupton 2016). Instagram in that way plays a double role in terms of self-measurement: it is used to share posts that display actual acts of measurement (e.g. a poster counting treatments), but it also serves as a social measuring instrument through visible interface scores—and algorithmic measurements less visible to users. Self-measurement has been a salient topic in digital research in media studies, sociology and cultural studies over the last five years and can be divided into two dominant strands—one which accentuates the contextually complex, ‘multivalent’ or ‘lively’ cultural roles of metrics (Lupton 2016; Neff and Nafus 2016; Pantzar and Ruckenstein 2017; Gerlitz 2016; Rettberg 2014; Day et al. 2014) and another which emphasizes their neoliberal and bio-political inclinations (Beer 2016; Crawford et  al. 2015; Ajana 2017) (cf. Chap. 1). In drawing on both of these strands, our aim in this chapter is not to judge social media metrics as either good or bad— or some as ‘vanity metrics’ aimed at measuring personal influence and others as ‘alternative metrics’ able to measure social movement and political potential (Rogers 2018)—but rather to explore and discuss how, and with what effects, self-measurement is involved in current forms of cancer storytelling on social media. Social media are of course not neutral channels where patients simply express their experiences. They are platforms with affordances that condition particular forms of narrative and quantified practices, and there are important narrative and interactional differences between specific platforms. Instagram, the core provider of material for this chapter’s analysis, was launched in 2010 and acquired by Facebook in 2012. Instagram is a ‘social networking site’ (SNS)—just like Twitter and Facebook—but it has its own characteristics and constraints. Firstly, in contrast to Facebook and Twitter, it gives prominence to visual communication (Ibrahim 2015). The name Instagram fuses ‘instant (camera)’ and ‘telegram’ and thereby underlines the immediate production and transmission of a combination of something visual with something written, which can be Liked, commented upon or shared on other platforms by followers, as its core form of communication. The relative brevity of the written input is supported by the fact that the maximum length of text in a post is 2200 characters. Content is restrained through rules regarding, for example, nudity and

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hate speech. Secondly, Instagram pushes users towards using mobile technologies like smartphones by making it difficult to upload pictures onto Instagram from the website and thus from laptops (Marwick 2015). The platform thus affords ‘networked photography’, which refers to ‘the practice of sharing photographs immediately after capture in real-time, mobile visual communication, using, for example, instant messaging (IM) tools or social media applications’ (Lobinger 2016, 475). Thirdly, Instagram— besides linking people with established strong ties (like the mutual friendship logic of Facebook)—prioritizes a more hierarchical or ‘unidirectional’ fan-like relation between ‘the followed’, who produce visual input, and ‘the followers’, who take on the role of responding to visuality through the heart or Like button or comments. Instagram also restrains the use of the platform through limitations regarding, for example, minimum age of profile owners (13  years) and maximum amount of images in a post, posts, Likes, comments, stories (cf. pictures and short recordings that are deleted after 24  hours), hashtags (that allow users to link posts to others posts) and follows/unfollows in a specific period of time. Furthermore, Instagram offers users with more than 10,000 followers special access to otherwise gated information (e.g. demographics of their users) and interface features (see Chap. 4). Focusing on the cultural implications of using the platform of Instagram, scholars have argued that it contributes to an ‘aestheticization’ of the mundane through ‘banal imaging’ (Ibrahim 2015). This fusion of aesthetics and everyday life has supported the rise of a new segment of talented entrepreneurial Influencers on Instagram with well-developed skills and competences in terms of visual presentation—and productions of selfies (Abidin 2016)—which are crucial for gaining popularity, or ‘instafame’ (Marwick 2015), on the platform (see Chap. 4). This point stresses that Instagram not only prioritizes a particular formal type of storytelling, based on visual, short and continuous narrative contributions, but also that it is more accessible for individuals with particular communicative and technological competences. This indirectly implies that specific patient groups (e.g. younger or well-educated patients), illnesses (e.g. well-known ones) and illness experiences (e.g. those able to transform into spectacular selfies) are more likely to be shared and spread well on Instagram.

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2.3   Methods and Material The chapter examines the self-measurement taking place on three public Instagram profiles made by female Danish cancer patients. The three profiles/cases are @jannelivsnyder66, made by Janne Hinrichsen (born 1966); @kristineelleby, made by Kristine Elleby Mølbæk (1987–2020); and @maikenbie, made by Maiken Bie Lindegaard (born 1989). None of the three profiles were initiated to share cancer experiences. Instead, they integrate illness into the flow of an existing profile due to a sudden diagnosis. In total, the sample consists of 1069 Instagram posts and comprises all available posts on the profiles at the time of sampling (Table 2.1). The profiles were followed by one of the authors for a longer period of time, and they were chosen and combined as characteristic examples of relatively ordinary patients’ use of quantified storytelling on social media (as opposed to the professionalized Influencers explored in Chap. 4). Furthermore, the cases are comparable in terms of size and period of use, but they are also different in terms of user profiles, their style of sharing, level of intimacy and ability to attract larger publics. By bringing them together we hope to offer an initial picture of different quantified uses of Instagram for narrating cancer experiences. This being said, it is crucial to maintain that social media are also cultural machines of (in)visibility by letting certain subjects, illnesses and experiences rise to the surface of collective attention more easily than others (Stage 2017). For that reason, it is important to stress that these three profiles, and looking towards Instagram as a platform in the first place, offer the researcher a very Table 2.1  Number of posts, comments, hearts and views on the three Instagram profiles, which are analysed in the chapter Profile and period

Posts

Comments

Hearts

Views

@jannelivsnyder Nov2015 Jun2018 @kristineelleby Aug2012 Apr2018 @maikenbie Jul2014 May2018 Total

n = 403

8597 Avg.: 21

96,789 Avg.: 240

n = 365

762 Avg.: 2

9571 Avg.: 26

n = 301

2478 Avg.: 8

46,698 Avg.: 155

n = 1069

11,837 Avg.: 11

153,058 Avg.: 143

137,363 Avg.: 763 (180 videos) 6560 Avg.: 328 (20 videos) 120,567 Avg.: 12056 (10 videos) 264,490 Avg.: 1259 (210 videos)

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particular perspective on having cancer in terms of class, race, gender, media literacy and national differences. The study is of course also too empirically limited to offer generalizations, but it instead provides in-­ depth understanding and theses about the narrative, quantified and interactional dynamics of narrating cancer experiences on social media and thus contributes with new knowledge to the budding field of social media illness narratives. To establish an overview of types of communicative forms, content and sharing practices—and changes during the lifespan of the three profiles— the material was processed through an explorative process of coding the 1069 posts. Some categories were established through theoretical typologies from existing research, while others were developed more inductively.2 All posts were categorized in order to identify potential relations between modes of sharing, including types of form/content and level of response, but most of all to get an impression of the profiles’ individual differences in ways of engaging with Instagram as a platform for sharing cancer experiences and to point out central or interesting posts, dilemmas or transformative moments in the life span of the singular profiles. To support the latter analysis, the profiles were divided into phases of before, during and (when possible) after cancer treatment. Concerning metrics, the number of Likes, comments and views of the singular posts and recordings were noted.3 Based on this, a list of the ten most commented and ten most Liked posts on each of the profiles were created. The role of metrics in the shared content—which is the key-interest of this chapter—was also registered, but primarily by taking notes in relation to particular posts where metrics were of importance. It is these observations and notes concerning metrics which will shape the forthcoming analysis and not the broader patterns of use on the three profiles. The three cases raise a range of important ethical questions. According to the 2002 and 2012 ethical recommendations of the Association of Internet Researchers (AoIR), what is ethically acceptable is highly dependent on the content, platform and context of the study (Ess and AoIR ethics working committee 2002, 4; Markham and Buchanan 2012, 4). An important ethical objective, however, is to ‘do no harm’ (Ess et al. 2002, 8), meaning that the research should result in no physical or psychological negative effects. Following this, the collection of empirical material is based on informed consent by the three female posters, who were also able to withdraw from the project at any time before publication. The users who commented on the Instagram profiles have been anonymized and

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translated (which makes it difficult to find the quote through a search) if quoted. Furthermore, we offered Janne, Kristine and Maiken the chance to read and comment on the chapter previous to its publication, which they all did without suggesting changes.

2.4   Analysis Stories of Teleological Counting and Hope Jannelivsnyder66—which could be translated as ‘Janneenjoyeroflife66’— made her first post on Instagram in November 2015, and her profile describes her everyday life but also the diagnosis and treatment of her second breast cancer experience and mastectomy. In terms of self-­ measurement, Janne, for instance, uses the profile to post pictures that produce a countdown to her final chemotherapy treatment. In the post from May 9, 2017, she shares an image of herself lying in a hospital bed displaying nine fingers to indicate that this is her ninth chemo treatment. The written caption states: ‘Yeaaaaah, now I am having the ninth chemo, 3 to go. F…., I’m looking forward to it’ and thus shows how the counting of treatments is not only an act of articulating how many parts of a whole the self has moved through (9 of 12), but also a way of affectively orientating the self (and the followers) towards the potential of a future where illness and treatment are less dominant. The post by Janne mentioned above receives 34 comments and 310 Likes and—like in many of Janne’s countdown posts—the commenting field expresses affective alignment as people share statements and emojis of tenderness, kisses and support, which Janne responds to by thanking and returning a similar affective statement or symbol. In this way, the act of counting treatments is entangled with a series of affective feedback loops, where Janne’s expressed happiness in the post is mirrored by loving comments that affect Janne, who then, in turn, expresses happiness as a result of the supportive comments. This clearly supports Zizi Papacharissi’s observation that social media publics often enable performative processes of affect production rather than simply acting as a repository for expressed affects. Affective publics allow users to ‘affectively tune into an evolving event or issue’ and thus create ‘particular forms or textures of affective attunement’ or continuous affective feedback loops in the sense that affective responses spur new responses (e.g. through their accumulation or

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rhythm), which then re-affects the starting point in new ways (Papacharissi 2015, 118). Kristine Elleby’s Instagram profile was established in 2012—the same year she first underwent surgery for a brain tumour. She had a second operation in 2013 and radiation therapy and chemotherapy treatment in the following years, after which she entered remission. However, in 2016, she suffered a serious relapse and, in 2017, she was told that her condition was incurable. Kristine died of her cancer disease in 2020. In the early years of the profile, cancer is—perhaps surprisingly—not a main topic. The first cancer-related content shared on the Instagram profile is an advert for a national collection day for the Danish Cancer Society (April 6, 2014). The second cancer post is shared on November 18, 2014, and shows a picture of the meal that Kristine had after a session of radiation therapy. Ten days later, Kristine shares the first selfie that visually and affectively positions her as a ‘hopeful patient’ (Giaxoglou 2020), as it depicts her happiness after having had 14 of 28 radiation treatments. This act of treatment measurement is shared through a picture of her smiling face and the text: ‘This is how you look when you have just had your fourteenth radiation treatment and are exactly a little bit over halfway AND are going to listen to @suspekt at Vega later on’. Both Janne and Kristine simultaneously share their counting of a treatment process (9 of 12 and 14 of 28) and their happiness at being near the end and halfway through their treatment, respectively. Kristine’s counting of radiation therapies in the post mentioned above, for instance, depicts the affective experience of moving through a particular treatment metrics with the end goal of ‘28’. The post furthermore expresses Kristine’s happiness at the same time as it produces a mediated affective encounter between her smiling face and her followers—an encounter that initiates a process of ritual alignment (Georgakopoulou 2016a) that seems to have an affective target (Anderson 2014): to support Kristine in her happiness and to maintain her motivation to move towards the final radiation treatment by underlining how cool, strong and beautiful she is. Traditional calendars also allow individuals to document their doings over time through the use of countable categories (months, days, hours), but the numerical difference between, for example, May 3 and May 4 is not necessarily of a narrative nature. Instead, this type of countable category is often a container for lists of disconnected events taking place on separate days. This disconnection of numerically coordinated events seems more difficult to uphold when the counting relates to the cancer diagnosis and treatment of a particular person. Here, the emblematic, highly

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reportable and culturally recognizable event of the cancer diagnosis in itself enacts expectations of specific archetypes (e.g. the warrior or fighter) and master plots (e.g. the restitution or quest narrative) (Shuman 2005). In others words, we all, due to previous unmediated and mediated encounters with stories of cancer, have rather extensive assumptions about the narratives that a diagnosed cancer patient can or will be able to tell. These expectations or master plots (Iversen and Pers 2020) seem to offer tellers and receivers narrative resources for understanding personal cancer experiences as having a more general or existential significance. Specific cancer experiences, therefore, very quickly acquire a ‘more-than-­personal meaning’ as stories of existential suffering and the human condition (Shuman 2005, 6). This swift move into the more-than-personal meaning of cancer experiences is also what gives the banal act of counting cancer treatments an almost inherent narrative quality, as readers very quickly embed counting in master plots of personal struggle against death. In counting cancer treatments on social media, this ‘interlocking’ of personal patient experiences with larger cancer master plots (Iversen and Pers 2020) can be either hinted at in singular posts as a potential (more could be told (Georgakopoulou 2013)), explicitly expressed or constructed over time by followers as they interweave singular posts with master plots through acts of reading. As mentioned, these narrative acts of counting the progressive movement of the self through a series of treatments can be interpreted as affective techniques used to both express and boost the patient’s own positive motivation, while creating approachable goals and hope in the process. They are in that sense also agentive (re)ownings of medically set targets, as measurement processes initiated in diagnostic and treatment encounters get entextualized, recontextualized and re-valorized on social media by the patients themselves. Counting treatment seems to work as what Beer describes as an ‘affective measure’ (Beer 2016)—a type of measure that affects and is felt by the body that it quantifies. Part of what boosts positivity and motivation is also how self-measurement produces a mediated encounter with follower bodies that respond by sharing their support—a type of response that is a general pattern on the profiles and thus also a possible aim of sharing these posts in the first place. In the two cases above, affects are thus partly produced in (1) a relationship between the metrics of a series of treatments and the self that measures its own progress and (2) a relationship between a self that narrates an act of measurement on social media and a group of followers who share their support to

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produce a kind of affective tailwind to help speed Janne and Kristine towards finalizing their treatments. Self-measurement in some sense tells a story with the aim of transforming the affective value of receiving chemotherapy and radiation treatment: Through an act of measuring the self, treatment is transformed into a moment of celebration and collective exchange of love rather than (only) a painful and distressing experience. In this sense, content metrics are in these examples what Nik Brown has called ‘metrics of hope’ (Brown 2015)—metrics that enable narrative and affective progression by presenting a future path of stages towards improvement and restored health. These treatment metrics thus seem to offer the patient an experience of already occurring, but also awaiting, progression and healing instead of a chaotic temporality of deep illness. They become part of what Ian Hacking has called ‘the taming of chance’ and thus of inserting a sense of probability into a highly unpredictable existential situation (Hacking 1990). And they are involved in affective encounters with social media users that support the progressive movement through these metrics of treatments, leading to potential closure and restitution. These self-measurement narratives handle the future in a particular way where it ‘is always already within the present; measured, planned for, determined’ in order to create a sense of agency in the ‘extended present’ (Coleman 2013, 101). Illness narratives based on teleological counting suggest ‘a linear progression from the present into the future, and the future, as a particular goal, is decided in advance’ (Coleman 2013, 104). Unfortunately, the future is always out of control, and the desire for linear progression thus first and foremost produces a feeling of potentiality, of a future maybe waiting to be lived despite illness. In these illness stories of teleological counting, the future is thus simultaneously controlled by envisioning future stages towards a cure and stressed as unpredictable, as this cure can only be anticipated. The levels of knowledge of Janne and Kristine as tellers are thus radically different from that of the author of a cancer autobiography that narrates an already experienced future. On the Instagram profiles mentioned, the future is always somewhat unpredictable and therefore the object of different strategies trying to master, map or forecast desired storylines and to enable processes of affective support and alignment.

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Stories of Frustrated (Re)Counting The smooth overlap between the happiness and loving optimism expressed and produced through sharing treatment metrics is based on a general cultural prioritization of restitution narratives (Frank 1995). As Sontag claims, serious illness should preferably be ‘moved through’ in order to arrive at the other side and hence to escape the ‘kingdom of illness’ (Sontag 1991). Sharing treatment metrics on social media reproduces this desire to travel through and escape the liminal sphere of serious illness. In the profiles examined, however, the longing for progression and closure is also often disturbed by measurement irregularities, pauses or adjustments caused by, for example, ineffective treatment or illness moving into a more aggressive phase. This can of course be communicated in different ways on social media—for example, by simply stating that treatment is not working—but looking at the three Instagram cases, a lack of progress often seems to produce a new adjusted, but also frustrating, process of counting due to the introduction of a different type of treatment or medicine. In this way, metrics are not only devices for performing progression but can also be ‘bad news’, when, for example, a new series of counting is announced or an old series is prolonged. These deferrals seem to motivate posts expressing anger and a feeling of not arriving at the desired goal. Maiken’s profile was established in 2014 and, at the time of sampling, contained 301 posts. In December 2016, Maiken was diagnosed with breast cancer, and in December 2017, she ended her treatment. Today she is cured of the disease. While Janne’s profile has a fun and warm style of sharing and Kristine foregrounds the laidback everyday aesthetics and young urban feeling of being a student in Copenhagen, Maiken’s profile is more visually dramatic and focuses on investigating the bodily aesthetics of undergoing cancer treatment. To some extent, it could also be said to have an entrepreneurial focus on manufacturing the perfect selfie prominent among the generation of increasingly famous Instagrammers described by Abidin (2016). In April 2017, Maiken shares a post in which metrics and self-­ measurement are linked to a sense of chaos and ‘being stuck’: Have just been to a meeting at the oncology unit—and I am fucking tired of this show. Here you are struggling your way through everything by focusing on the fact that you will be finishing chemo “in just a moment”— then you’ll get your life back. But no, you don’t, not at all. (…) I have to

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begin antihormonal treatment after the chemo (…)—and that will be for 10 years. 10 years! (April 24, 2017).

This exemplifies how one narrative goal already accepted by Maiken (‘finishing chemo’) is disturbed by a new and much longer process of treatment (ten years of antihormonal treatment). What is seemingly at stake here is the agency of Maiken and her capacity to escape the illness and its systems through some sort of control and ability to navigate her way into the future. The repetition of ‘10 years’, and the added exclamation mark, suggests that the awaiting years of treatment suddenly feels overwhelming as it threatens to make illness and treatment a permanent part of the self rather than a phase she can tell her way out of (cf. ‘in just a moment’). This exemplifies that stories of teleological counting can quickly be transformed into frustrated stories when timelines are shifted and new measurement processes are initiated that threaten a sense of subjective agency and narrative progression. Another post from the very beginning of Maiken’s chemotherapy treatment clearly expresses the tension between (1) using metrics to create a controllable future that enables the self to navigate the movement from being ill in the present to (hopefully) being cured and (2) feeling stuck in a process of counting that stalls movement and threatens to permanently position the self as seriously ill. In this post, Maiken writes: Yes, now she is talking about that hair again. You might as well be patient because my hair will be the center of attention over the next two weeks. Now you know. Tomorrow will be 1 week since the first chemo—the experts claim that my hair will fall out after 14 days approximately (of course not like: BOOM suddenly all the hair is gone, but more that large chunks of hair will fall out when you pull a brush through it). My hair is 69 cm long— Google claims that hair grows at an annual average of 12 cm. I have done a bit of calculating: It will take 5.75 years to grow out again (if it is not cut at any point that is). 5.75 years! (January 22, 2017)

This measurement post expresses Maiken’s interest in striking and innovative visuals, and it shows how metrics are both navigational devices that make the future less chaotic and a potential source of fear and frustration. The post uses the measurement of days and hair to position the self in a differentiated time of causal development and to signal to the followers that future posts will have a key-theme (losing hair) and adhere to a

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more sequential logic with a beginning (long hair and chemo treatment), middle (hair falling out) and end (lack of hair). It also suggests a future storyline for the profile over the following five years or more, as it will possibly engage in a process of self-tracking, while she attempts to grow her hair to the exact same length as before the chemotherapy treatment. Maiken’s attempt to master the unpredictability of the future with serious illness through the measuring tape is intertwined with a sense of frustration expressed through repeating ‘5.75 years!’ and once again adding an exclamation mark. The future—and the loss of hair, including the loss of identity it seems to incarnate—might be easier to comprehend, when made countable, but it also suddenly seems like a state of being, which is difficult to see past. In a sense, performing the calculation of 5.75 years oscillates between being used to produce an affective target—optimism as the hair will eventually grow back—and being an affective encounter in itself: facing this specific amount of years produces an affect of slight resignation or being overwhelmed. In the case of Kristine, treatment metrics become frustrating and saturated with fear for a very different reason: the illness keeps returning and demands evermore treatments that prolong the liminal sphere of illness. On January 7, 2018, she writes: I have been going between sleeping and throwing up for the last 48 hours. This chemo series is the last attempt, and, even though it hurts to fill your body with poison, it is the thought that it might also not work this time which hurts the most.

After numerous relapses, the simple idea of ‘moving through’ illness via successive steps of treatment no longer seems completely trustworthy for Kristine. Instead, counting treatments becomes saturated with fear and worries about not being able to restore health. The narrative logic of restitution is threatened by a narrative logic of chaos (Frank 1995) as the notion of being able to count her way through treatment becomes less and less likely. Chaos is precisely chaos because it cannot be mapped or organized in stages through which you can move and count your way. Chaos instead produces eternal counting or the impossibility of counting. Paradoxically, reaching the narrative goal of being cured can also produce its own frustrations, as shown in the following section.

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Performative Measures of Positivity and the Tellability Crisis of Having Nothing to Count The interaction on the three Instagram profiles can be analytically approached by focusing on the interplay between three co-­constitutive levels: 1. The level of the desired illness narrative and position that the narrator hopes to be able to tell. The narrative in such cases tends to be focused on progressing towards a cure and expressed in bios or singular, more programmatic posts. This narrative desire is highly influenced by available cultural categories (Shuman 2005), master plots, understood as ‘recurrent skeletal stories’ (following Abbott) or as ‘a subset of culturally shaped and culturally shaping stories that exists on a transindividual level but has effect on the individual level’ (Iversen and Pers 2020, 9), and interaction with followers. 2. The level of everyday posts sharing moments more or less directly related to illness experiences, which can either help maintain or disturb the desired narrative. 3. The level of quantified follower responses (through scores of hearts/ Likes and comments), where the alignment of the desired narrative and the singular posts are often monitored (Stage 2019b). An important point is that none of the three levels are stable or created outside social interaction. For instance, the level of the desired narrative is not about simply expressing the inner thoughts of the ill person. Instead, it is co-constructed and renegotiated through day-to-day communication with interlocutors and available cultural master plots. Turning to Janne, she very explicitly describes the desired or intended narrative that she wants to tell about her illness, but also the type of subject position she aligns herself with. Clearly, her ideal narrative is what Arthur Franks has described as the ‘restitution narrative’ (Frank 1995)—a master plot where illness moves from diagnosis to treatment to cure—but more importantly, Janne wants to tell the story of how this process of treatment and struggle can also be filled with joy and happiness. And her followers constantly validate that she is an extraordinarily positive, happy and funny person in the comments through ritual appreciation. In the profile bio, Janne positions herself as a positive and somewhat hedonistic person (cf. the name of the profile and the wine emoji)—and, perhaps less consciously, as not overtly focused on perfection (cf. a lack of focus on

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typos). This self-positioning is also expressed in singular posts where her overall existential and affective approach to life—along with her confirmation of the importance of user response—becomes an explicit theme: Just took a 7,4 km chemo-walk. No pain. Head is tired, but not the body. Spirit is high. The sun is shining. Life is great. And thank you so much to all of you following me. It is just as much you, who makes me wanna share something on Instragram. I want to show, how important it is to stay happy and keep believing in life. Lots of fighting spirit. Humor, happiness, a positive mind, exercise, support from family and friends are invaluable things. And once in a while you should be allowed to be a little crazy and childish although you are 50 years old. (March 28, 2017)

An important part of her affective positioning (Giaxoglou 2015) is also expressed through optimistic pictures and selfies of her bare-chested or scarred body. They likewise serve to underline the happiness and pragmatic vitality of Janne. A bare-chested picture from May 17, 2018, is, for instance, accompanied by a text describing all the health problems that Janne has had with her breasts over the years and how happy she therefore is to have gotten rid of them. This visual focus on scar images and selfies—and the female body living happily without breasts—gives the profile an almost activist touch as Janne takes control over the visual appearance of her wounded body (Tiidenberg and Cruz 2015; Tembeck 2016). It incarnates the ideal of Audre Lorde’s classic The Cancer Journals (1980) in which Lorde argued in favour of women with cancer quitting their prostheses and taking the scarred, bald, asymmetrically curved or flat body into the public sphere (Lorde 1997). And this line of everyday body activism is clearly supported by Janne’s followers and measured through interface metrics. If we take a look at the ten most Liked posts, seven of them (marked with *) are images showing Janne as bare-chested—with one or two breasts removed—while smiling (Table 2.2). In that way, liking seems to be particularly intense on the profile, when posts express an image of the embodied self, and of its approach to serious illness, that is aligned with the desired narrative of positivity and the master plot of the restitution narrative. Through these peaks of liking, followers thus support the continuous co-production of Janne’s identity as happy and optimistic, even during the hardships of cancer, and thus create a feedback loop of positivity where particular affective approaches to illness are praised through numbers/scores and afforded if the teller wants to

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Table 2.2  The ten most Liked posts on the profile Jannelivsnyder66 Likes/ hearts

Content

Illness phase

1198*

Picture of scar from first mastectomy (18/8/2016)

1076*

Officially cured of the disease (8/7/2017)

912

Last chemo treatment (30/5/2017)

880*

Drinking and liking a beer (21/7/2017)

827*

In a week my breast is removed and I don’t care (21/6/2017) Scar after second mastectomy (29/6/2017)

Before (second) illness After (second) illness During (second) illness After (second) illness During (second) illness During (second) illness After (second) illness During (second) illness After (second) illness After (second) illness

695* 658 480 472* 456*

Preparing a public talk about my cancer process (4/10/2017) Chemo 10 out of 12—only 2 to go (16/5/2017) The history of my breasts and why I can live without them (17/5/2018) Happy and bare-chested Janne under an umbrella (16/7/2017)

receive more positive response. The value of positivity is thus expressed and performatively produced through interface metrics. The intense response to these scar images is also culturally conditioned: on the one hand, they are visually provoking by showing the flat and bare-­ chested female body, which is still a rare image, but on the other hand, they resonate with a cultural reverence for cancer patients able to affectively transgress their illness, stay happy or perform vital actions of survival and struggle (Rose 2006; Seale 2002; Stacey 1997; Ahmed 2010). Janne’s most Liked selfies are thus both culturally provoking and culturally desired at the same time: they allow women to embrace the scarred and non-­ prosthetic body, but the intensified liking also seems to support the notion that happy cancer patients should be praised and acknowledged. The smooth alignment of (1) the desired narrative and subject position; (2) the content of the shared post; and (3) follower responses through metricized performative liking is sometimes disturbed. This happens when the shared moment in the post is not corresponding with the desired

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narrative of restitution and happiness. An example is from May 29, 2017, which is the day before Janne’s last chemo treatment. Here the post is not focused on progress towards a cure and happiness, but rather shares a small story4 of sadness, disappointment, but also of a potential return to a more positive state in the near future: Off day, right from the very beginning. Couldn’t wake up, when I left my bed. Started freezing, madly, after breakfast as a sign of fever. I quickly took some painkillers, and the fever dropped. Just thought that it was really irritating as I was laying there feeling sorry for myself. I should have attended a Lady Walk together with my lovely friends, but regrettably I can’t. I have slept a little, and feel a little better, but I prefer to stay in bed the rest of the day. Hopefully I will be ready for the last chemo, tomorrow. (May 29, 2017)

This kind of post that disturbs and, in some sense, threatens the narrative and affective self-understanding constructed previously through interaction on the profile apparently cannot simply be Liked (or given a heart), but it calls for a comment.5 Comparing the ten most Liked posts with the ten most commented posts there are several overlaps (four posts to be precise), but while the list of ‘most Liked’ primarily consists of posts presenting news of progression that can be supported, while the ‘most commented’ list also consists of posts where progress is momentarily threatened or stalled. Some of the comments to the above-quoted post are: –– So sorry Janne. Thinking of you and I am sure that you will be completely ready for tomorrow –– Sweetest girl …. Luckily most days treat you well—and tomorrow it will be gone—so stay strong –– Hugs for you . Today you need to stay in bed. Tomorrow will be a new day These comments are characterized by ‘supportive disalignment’ (Stage 2019b), where commenters do not align with the predominant negativity of the post but try to transform its affective quality by focusing on negativity as momentary, as a small bump in the road leading to a happy end. The commenters thus insist that the post should be interpreted within a larger narrative framework of restitution and that it has to be approached as a temporary digression. In that way, commenters through supportive disalignment try to reconnect or realign Janne with the previously

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constructed subject position focused on progression and happiness—a process of realignment that she signals being open to with the concluding sentence on a hopefully better tomorrow. This underlines that Janne is not simply telling her ‘own’ story—she is telling it together with her followers and influenced by more or less tacit norms about, which version of her story is more culturally acceptable and valorized. And sometimes her followers actually take the lead by telling the story about Janne as a happy and optimistic patient to Janne if she forgets or starts doubting it. If posts over a period divert from the desired narrative, it can be argued that the poster is forced to engage in acts of repositioning the overall story he or she hopes to be able to tell in the future. This actually happens after Janne is officially cured. For Janne, the introduction of serious illness on her profile increases her story’s tellability in relation to a particular audience of other cancer patients (often sharing their own illness stories in comments) or followers interested in the disease. A rather peculiar narrative situation is therefore created as Janne’s treatment process finishes and counting her treatment therefore stops. This moment causes what Stage has called a ‘tellability crisis’ (Stage 2019b), as the drama of fighting death is replaced with more mundane occurrences of living a normal life. Janne addresses this quite explicitly in a post: This morning I ran 3,7 km. Really nice. I hope that you want to help me a little bit. I am not so enthusiastic about Instragram at the moment. I can’t figure out if I should share something as a normal cured person or if I should continue with something related to breast cancer and the life I am now leading as a former breast cancer patient. What do you think? (April 28, 2018)

The sentence expresses an experience of disconnection between the life of Janne, the platformed narrative affordances of Instagram and the collective contract established between herself and her followers regarding what is worth telling on the profile. The former happiness created by the smooth, positive and self-perpetuating collaboration between Janne and the followers during her crisis is replaced by a frustrating misfit between the logic of the platform (cf. ongoing sharing of emblematic and recent updates able to attract the attention of large audiences), Janne’s life (not always much to tell as a cured person), the interests of many of the followers (to engage in existential support during crisis) and cancer master plots (after restitution, the story of illness ends). Therefore Janne is not sure

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what to share and what position to inhabit as a teller: the former breast cancer patient or the normal cured person? In a sense, Janne’s post continues the act of self-tracking (now focusing on exercise and improving health instead of fighting illness), but the larger process of counting the stages towards being cured is at an end. And as such Janne will have to reposition herself in relation to her audience—or rather to engage in social interaction with followers about how they perceive her and how she should communicatively position herself. The post is interesting because it indirectly acknowledges that reaching the goal of being well creates a fundamental relational problem between Janne and her followers: If we are following you due to your fight against cancer, but you no longer have cancer, why are we following you? Janne faces this crisis of tellability by inviting the followers to co-create what should now be the logic of affective and narrative exchange on the profile. In the 34 comments to the post, Janne’s followers primarily want her to ‘be herself’ and share whatever she feels like. One follower acknowledges the ambivalent position of Janne as a teller and suggests that she should perhaps have two profiles: one for cancer-related material and one for everyday moments, but Janne finds that too confusing and thereby stresses her desire to use the profile to tell the story of a coherent self despite her increasing insecurities about how to do this. The example illustrates that social media cancer profiles are often characterized by shifting phases of tellability in relation to particular groups of audiences. The tellability crisis can also be described as the consequence of a movement between two distinct practices of self-measurement. As mentioned in Chap. 1, Neff and Nafus distinguish between measurement as ‘self-tracking’ (with the aim of transforming the self by reaching a goal) and ‘life-logging’ (with self-reflection as the main goal). With her cancer diagnosis, Janne seems to move from a mode of life-logging, where everyday moments are documented, to a mode of self-tracking by increasingly focusing on the telos of the last chemo/being cured, while the post above signals her move back into a mode of life-logging after treatment has ended. Serious illness as an ongoing and measurable experience, segmentable in targets, seems to afford a process of self-tracking that resonates well with platform affordances of brevity, breaking news and immediacy and is able to attract increased follower attention. Janne’s life after treatment, characterized by less defined and trackable stages, instead seems to call for a quantified storytelling practice of logging (cf. measuring kilometres for no particular reason), which creates a less affectively intense

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relationship with her followers and demands a repositioning of herself as a teller. Janne’s lack of enthusiasm about Instagram ‘at the moment’ is therefore also indicative of her arrival into a new narrative situation, which calls for a more mundane mode of storytelling as life is no longer reportable due to emblematic processes of illness.

2.5   Conclusion In this chapter, we have argued that one of the ways metrics are increasingly important for storytelling practices on social media is through acts of self-measurement in the content shared by posters. Self-measurements thus seem to be important navigational devices in terms of trying to process and reclaim a sense of agency during an existential crisis. On a content level, numbers are, as shown, taken up in (cancer) stories on social media as an inherent part of the temporal progression of the narrative towards a less chaotic future. This existential navigation through numerical storytelling resonates with the platformed affordances of Instagram, which are designed to extract value from the circulatory power of visually dramatic, ongoing, emblematic, brief, affectively engaging (cf. the heart button) and embodied posts (e.g. selfies) that invite followers to interact, Like and comment in empathetic and supportive ways. This stresses that cancer storytelling on Instagram both shape and are shaped by media ecologies characterized by complex subjective, affective and economic orders of worth, but also that counting practices seems to be an effective way of adapting cancer storytelling to platformed logics and constraints. Due to the platformed push towards ongoing, recent, visual and brief acts of storytelling, it could be argued that counting becomes an almost optimal way of telling and showing restitution narratives on social media. If you want to narrate restitution processes on social media, you will very likely have to count in order to create a sense of succession and movement between treatments that are often identical and difficult to separate from each other. These treatments are in a sense ‘unreportable’ if the teller does not continuously enact the overall telos of the process of ongoing sharing (cf. being cured/ avoiding death), and this is exactly done by counting stages and positioning the self as progressively moving through them. In the cases explored in this chapter, cancer stories thus primarily focus on temporal progression towards a telos (recovery) and on tracking the development of the self on its journey towards a cure. Within this line of

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thinking, measurements are often aimed at producing hope, and they invite followers to engage in processes of affective alignment that supports the overall movement towards a cure and maybe even keeps the teller in sync with the ideal of recovery during times of struggle or doubt. This teleological logic can be disturbed and cause various forms of more or less fearful frustration if progression is either stalled and counting needs to start all over or even if it reaches its goal and there is nothing more to count. Here platform affordances and the life of tellers often disconnect as restitution is either projected too far into an opaque future or actually obtained, thereby obstructing the narrative attraction of travelling through illness. Ending on a more critical note, it could be argued that the constant focus and collective appraisal of ongoing, visual documentations of positivity-­ in-crisis, which is supported by teleological counting and Instagram affordances, also reproduce already widespread and problematic illness discourses that prioritize the value of the happy, forward-­ moving and entrepreneurial patient (Mol 2008; Stacey 1997; Stage 2017). Through this lens, self-measurement on cancer profiles—and the affective processes it affords—might also contribute to a bio-political condition that stresses vitality, optimism and a constant personal struggle and responsibility for improvement and effectivization as the desired patient position. Quantified self-tracking in that way seems to have become a crucial device for narrating, visualizing and sensing the self and body with cancer during dramatic times of transformation and crisis, but also for reproducing limited notions of culturally desirable patient behaviour.

Notes 1. https://www.youtube.com/watch?v=MvG3ifEd0t0 2. All posts were categorized according to the following categories: (1) Type of content: Through engaging inductively with the posts five primary content categories were established: a category for posts dealing with treatment and their effects (e.g. getting and being tired after chemo); a category for posts sharing jokes or other types of humorous content; a category of banal images showing everyday life in an aestheticized way; an existential category for posts dealing with fundamental issues of death, survival and the fundamental change of or threat towards the self and identity of the narrator; a category for posts dealing with specific bodily performances (running, fitness etc.) or the effect of them (e.g. showing muscles, sweating) and a sixth other

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category for the relatively few posts not fitting into these five specific categories. (2) Mode of sharing: Is the post shared to start a conversation (cf. does it have the role of asking a question), to communicate information about something or is it of a more phatic character, where the post is not communicating information about moments, events or the self, but serving the role of establishing and maintaining contact with followers (Lobinger 2016)? (3) Use of selfies: Is the shared image a selfie (understood as a picture that the poster has taken of herself (cf. not visual recordings)) and if so, is the selfie a me selfie, a significant other selfie or a group selfie (Georgakopoulou 2016b)? (4) Affective tone: Is the overall affective tone or spirit of the post positive, neutral, negative or other? 3. Views were not counted on Instagram before 2016. 4. Disjuncts between a canonical, expected narrative and the tellers’ making sense of their experience have commonly been reported in narrative interview research, where small stories have been found to be the genre of choice for tellers’ more or less explicit departures and countering of norms in narrating themselves (for an overview of this work, see Georgakopoulou 2015). 5. In a similar vein, Georgakopoulou (2017) found a close association between Facebook statuses that reported complications in the poster’s life and comments in contrast to the reporting of mundane events that routinely only elicited Likes (and reactions).

References Abidin, Crystal. 2016. “Aren’t These Just Young, Rich Women Doing Vain Things Online?”: Influencer Selfies as Subversive Frivolity. Social Media + Society, April–June 1–17. Ahmed, Sara. 2004. The Cultural Politics of Emotion. Edinburgh: Edinburgh University Press. ———. 2010. The Promise of Happiness. Durham: Duke University Press. Ajana, Btihaj. 2017. Digital Health and the Biopolitics of the Quantified Self. Digital Health 3: 1–18. Alzheimer Europe. 2011. The Value of Knowing. Alzheimer Europe. Anderson, Ben. 2014. Encountering Affect. Capacities, Apparatuses, Conditions. Abingdon: Ashgate. Andersson, Yvonne. 2017. Blogs and the Art of Dying: Blogging With, and About, Severe Cancer in Late Modern Swedish Society. OMEGA 1–20. Arduser, Lora. 2017. Remediating Diagnosis. In Emerging Genres in New Media Environments, ed. Carolyn Miller and Ashley Kelly. Cham: Palgrave. Bamberg, Michael. 2016. Narrative. In The International Encyclopedia of Communication Theory and Philosophy, ed. K.B. Jensen and T.T. Craig. Oxford: John Wiley & Sons, Inc.

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Beer, David. 2016. Metric Power. Basingstoke: Palgrave. Bolaki, Stella. 2016. Illness as Many Narratives. Edinburgh: Edinburgh University Press. Brown, Nik. 2015. Metrics of Hope: Disciplining Affect in Oncology. Health 19 (2): 119–136. Bury, Michael. 1982. Chronic Illness as Biographical Disruption. Sociology of Health and Illness 2 (4): 167–182. Charon, Rita. 2006. Narrative Medicine. Honoring the Stories of Illness. New York: Oxford University Press. Coleman, Rebecca. 2013. Transforming Images. Screens, Affects, Futures. New York: Routledge. Coll-Planas, Gerard, and Mariona Visa. 2016. The Wounded Blogger: Analysis of Narratives by Women with Breast Cancer. Sociology of Health and Illness 38 (6): 884–898. Couser, G. Thomas. 2016. Body Language: Illness, Disability, and Life Writing. Life Writing 13 (1): 3–10. Crawford, Kate, Jessa Lingel, and Tero Karppi. 2015. Our metrics, Ourselves: A Hundred Years of Self-Tracking from the Weight Scale to the Wrist Wearable Device. European Journal of Cultural Studies 18 (4-5): 479–496. Davis, Jenny, and James Chouinard. 2016. Theorizing Affordances: From Request to Refuse. Bulletin of Science, Technology & Society 36 (4): 241–248. Day, Sophie, Celia Lury, and Nina Wakeford. 2014. Number Ecologies: Numbers and Numbering Practices. Distinktion: Scandinavian Journal of Social Theory 15 (2): 123–154. Ess, Charles, and AoIR Ethics Working Committee. 2002. Ethical Decision-­ Making and Internet Research. Recommendations from the AoIR Ethics Working Committee. AoIR. Finn, ed. 2017. What Algorithms Want. London: MIT Press. Frank, Arthur W. 1995. The Wounded Storyteller. Chicago: Chicago University Press. ———. 1998. Just Listening: Narrative and Deep Illness. Families, Systems & Health 16 (3): 197–212. Georgakopoulou, Alexandra. 2013. Small Stories Research and Social Media. Working Papers in Urban Language and Literacies 100: 1–18. ———. 2015. Small Stories Research: Issues, Methods, Applications. In Handbook of Narrative Analysis, ed. Anna De Fina and Alexandra Georgakopoulou, 255–271. Malden, MA: Wiley-Blackwell. ———. 2016a. ‘Friendly’ Comments. Interactional Displays of Alignment on Facebook and YouTube. In Discourse and Identification: Diversity and Heterogeneity in Social Media Practices, ed. Sirpa Leppanen, Samu Kytola, and Elina Westinen. New York: Routledge. ———. 2016b. From Narrating the Self to Posting Self(ies): A small Stories Approach to Selfies. Open Linguistics 2: 300–317.

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———. 2017. Life/Narrative of the Moment. From Telling a Story to Taking a Narrative Stance. In Life and Narrative. The Risks and Responsibilities of Storying Experience, ed. B. Schiff, E. McKim, and S. Patron, 29–54. OUP. Gerlitz, Carolin. 2016. What Counts? Reflections on the Multivalence of Social Media Data. Digital Culture and Society 2 (2): 19–38. Giaxoglou, Korina. 2015. ‘Everywhere I go, You’re Going with Me’: Time and Space Deixis as Affective Positioning Resources in Shared Moments of Digital Mourning. Discourse, Context and Media 9: 55–63. ———. 2020. A Narrative Approach to Social Media Mourning. Small Stories and Affective Positioning. London: Routledge. Hacking, Ian. 1990. The Taming of Chance. Cambridge: Cambridge University Press. Hardey, Michael. 2002. ‘The Story of My Illness’: Personal Accounts of Illness on the Internet. Health 6 (1): 31–46. Hawkins, Anne Hunsaker. 1999. Reconstructing Illness. Studies in Pathography. West Lafayette: Purdue University Press. Heilferty, Catherine. 2018. The Search for Balance: Prolonged Uncertainty in Parent Blogs of Childhood Cancer. Journal of Family Nursing 1–21. Henriksen, Nina. 2014. Hjemløsheden, rejsen og den kronotopiske identitet - en litteraturteoretisk analyse af en selvbiografisk kræftfortælling. Tidsskrift for Forskning i Sygdom og Samfund 20: 113–143. Humphreys, L. 2018. The Qualified Self: Social media and the Cataloguing of Everyday Life. Cambridge: MIT Press. Hydén, Lars-Christer. 1997. Illness and Narrative. Sociology of Health and Illness 19 (1): 48–69. Ibrahim, Yasmin. 2015. Instagramming Life: Banal Imaging and the Poetics of the Everyday. Journal of Media Practice 16 (1): 42–54. Iversen, Stefan, and Mikka Lene Pers. 2020. Interlocking Narratives: The Personal Story and the Masterplot in Political Rhetoric. In Exploring Fictionality: Conceptions, Test Cases, Discussions, ed. Maagaard et al. Odense: Odense University Press. Jurecic, Ann. 2012. Illness as Narrative. Pittsburgh: University of Pittsburgh Press. Kaplan, Andreas, and Michael Haenlein. 2010. Users of the World, Unite! The Challenges and Opportunities of Social Media. Business Horizons 53: 59–68. Klastrup, Lisbeth. 2016. Sociale netværksmedier. København: Samfundslitteratur. Kleinman, Arthur. 1988. The Illness Narratives. New York: Basic Books. Lobinger, Katharina. 2016. Photographs as Things – Photographs of Things. A Texto-Material Perspective on Photo-Sharing Practices. Information, Communication & Society 19 (4): 475–488. Lorde, Audre. 1997. The Cancer Journals. Special ed. San Francisco: Aunt Lute Books. Lupton, Deborah. 2016. The Quantified Self. Cambridge: Polity.

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Markham, Annette, and Elizabeth Buchanan. 2012. Ethical Decision-Making and Internet Research. Recommendations from the AoIR ethics working committee (Version 2.0). AoIR. Marwick, Alice. 2015. Instafame: Luxury Selfies in the Attention Economy. Public Culture 27 (1): 137–160. Mattingly, Cheryl. 1998. Healing Dramas and Clinical Plots. Cambridge: Cambridge University Press. McCosker, Anthony. 2017. Data Literacies for the Postdemographic Social Media Self. First Monday 22 (10). Mol, Annemarie. 2008. The Logic of Care. Health and the Problem of Patient Choice. London and New York: Routledge. Neff, Gina, and Dawn Nafus. 2016. Self-tracking. Cambridge: MIT Press. Nesby, Linda, and Anita Salamonsen. 2016. Youth Blogging and Serious Illness. Medical Humanities 42: 46–51. Ochs, Elinor, and Lisa Capps. 2002. Living Narrative. Creating Lives in Everyday Storytelling. Cambridge: Harvard University Press. Orgad, Shani. 2005. Storytelling Online. Talking Breast Cancer on the Internet. New York: Peter Lang. Page, Ruth. 2012. Stories and Social Media. Identities and Interaction. New York: Routledge. Pantzar, Mika, and Minna Ruckenstein. 2017. Living the Metrics: Self-tracking and Situated Objectivity. The Senses and Digital Health 3: 1–10. Papacharissi, Zizi. 2015. Affective Publics: Sentiment, Technology, and Politics. New York: Oxford University Press. Pitts, Victoria. 2004. Illness and Internet Empowerment: Writing and Reading Breast Cancer in Cyberspace. Health 8 (1): 33–59. Rettberg, Jill Walker. 2014. Seeing Ourselves Through Technology. Basingstoke: Palgrave. Rogers, Richard. 2018. Otherwise Engaged: Social Media from Vanity Metrics to Critical Analytics. International Journal of Communication 12: 450–472. Rose, Nikolas. 2006. The Politics of Life Itself. In Biomedicine, Power, and Subjectivity in the Twenty-First Century. Princeton: Princeton University Press. Seale, Clive. 2002. Cancer Heroics: A Study of News Reports with Particular Reference to Gender. Sociology 36 (1): 107–126. Shapiro, Johanna, Jack Coulehan, Delese Wear, and Martha Montello. 2009. Medical Humanities and Their discontents. Definitions, Critiques, and Implications. Medical Humanities 84 (2): 192–198. Shuman, Amy. 2005. Other People’s Stories. Urbana and Chicago: University of Illinois Press. Skott, Carola. 2002. Expressive Metaphors in Cancer Narratives. Cancer Nursing 25 (3): 230–235. Sontag, Susan. 1991. Illness as Metaphor. London: Penguin Books.

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Stacey, Jackie. 1997. Teratologies. A Cultural Study of Cancer. London: Routledge. Stage, Carsten. 2017. Networked Cancer. Affect, Narrative and Measurement. Basingstoke: Palgrave. ———. 2019a. Affective Measures: Self-measurement and Gridding in Female Cancer Patients’ Storytelling Practices on Instagram. Distinktion 20 (1): 77–100. ———. 2019b. Cancer Narratives on Social Media as ‘Small Stories’: An Investigation of Positioning, Supportive (Dis)alignment and Tellability Crises in Cancer Storytelling on Instagram. Journal of Research in Sickness and Society 16 (31): 269–286. Tembeck, Tamar. 2016. Selfies of Ill Health: Online Autopathographic Photograpgy and the Dramaturgy of the Everyday. SM+S  – Social Media + Society, January–March, 1–11. ———. 2017. Autopathographies in New Media Environments at the Turn of the 21st Century. In Emerging Genres is New Media Environments, ed. Carolyn Miller and Ashley Kelly. Cham: Palgrave. Tiidenberg, Katrin, and Edgar Gómez Cruz. 2015. Selfies, Image and the Re-making of the Body. Body & Society 21 (4): 77–102. van Dijck, José, Thomas Poell, and Thomas de Waal. 2018. The Platform Society. Public Values in a Connective World. Oxford University Press: New York. Williams, Simon J. 2000. Chronic Illness as Biographical Disruption or Biographical Disruption as Chronic Illness? Sociology of Health and Illness 22 (1): 40–67.

CHAPTER 3

Making Memes Count: Platformed Rallying on Reddit

3.1   Introduction In this chapter, we shift our focus from the personalized storytelling practices on Instagram to the heated collective interaction of a social media public. Our object of study is what is known as the ‘The_Donald’ (TD) on the website www.reddit.com. TD is a so-called subreddit, one of the many individual, user-created and user-maintained thematically structured subsections that make up reddit. A subreddit is somewhat comparable to a message board in that it lets users post, comment on posts and vote on posts once they have created a pseudonymous avatar. TD was established in June 2015 with reference to Donald Trump’s campaign for the presidency, and at the time of writing this (November 2019) it counts approximately 800,000 members, with approximately 6500 online at any given time.1 The subreddit currently holds more than 4,000,000 user-submitted posts and more than 40,000,000 user comments to those posts, making TD one of the most active subreddits on what is one of the biggest (in terms of engagement and traffic) websites in the world. As a cultural phenomenon, TD is interesting because of its extreme nature: the subreddit has developed an extremely peculiar and immediately recognizable discursive practice through which extreme political and ideological views are uttered. The rhetoric is ambivalent on several levels: it is both extremely introvert, almost private, and very invested in breaking through to and influencing how meaning develops in larger publics; it is both deeply ironic and deadly serious. As an object © The Author(s) 2020 A. Georgakopoulou et al., Quantified Storytelling, https://doi.org/10.1007/978-3-030-48074-5_3

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of study in relation to our investigation of how stories and metricization interact on digital platforms, TD is interesting because of the narrative strategies employed by this particular public. These strategies are not merely affected by the metricized affordances of the reddit platform. They can also be said to adapt their storytelling practices to the algorithmic realities of the platform, while also influencing how these realities develop (Bucher 2018). We want to approach an understanding of TD as a form of platformed rally. Key to its meaning-making processes are specific forms of platformed narrating in the shape of what we, in dialogue with research on digital memes (Shifman 2014), will call incongruous rescriptings and reflexive quantified storytelling. The first is characterized by creative and fragmented reframings and recirculations of existing media material in narrative form through parody, exaggeration, fictionalization and defamiliarization. Quantified storytelling designates stories about numbers, numbered story responses and the algorithmic shaping of stories. In this chapter, we zoom in on a more reflexive form of ‘stories about numbers’, where the numbers that make up the story originate in the story’s own circulation. The chapter undertakes a close textual analysis of examples of these two forms of narrating after discussing, first, the metricized affordances of reddit as a platform and, second, the nature of what TD is in relation to ideas about online communities, counterpublics and online crowds and how one might approach a study of it.

3.2   The Metricized Affordances of Reddit In this section, we set out to (a) give a general description of what reddit is, (b) consider how the platform on a general level is metricized and (c) analyse what we take to be the three key-affordances of the platform: the status of subreddits as individual entities, the point score and the anonymity of users. According to alexa.com, www.reddit.com is the sixth biggest website in the United States, with users spending an average of 8:31 minutes daily on the site.2 Different attempts at describing the particularities of the platform compared to other types of social media exist. As noted by Kilgo et al. (2018, 2), some refer to it as a social networking site or social news aggregator (Bergstrom 2011) and others as a social news site (Suran and Kilgo 2017). Squirrell characterizes it as combining ‘the affordances of social media (shareability, networked groups, algorithmic newsfeeds; boyd

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2010) and early Internet message boards and Usenet groups (anonymity, volunteer moderation and subject specificity; Baym 1999)’ (Squirrell 2019, 1911). In contrast to Instagram, Facebook and Twitter, on reddit you connect yourself to and follow themes rather than individuals, but interactions are more segmented than the open searchable archive of, for example, YouTube. In addition, the co-created output is not a shared collaborative text as on, for example, Wikipedia, but rather collectively ranked contributions made by anonymous users. In the words of the platform, ‘reddit is a source for what’s new and popular on the web. Users like you provide all of the content and decide, through voting, what’s good and what’s junk’ (https://www.reddit.com/wiki/faq, 160518). The site is divided into more than 130,000 separate, persistent boards, known as subreddits, each covering one of a very wide range of topics and each moderated by a small group of super-users. Moderators may then communicate through either closed subreddits or using other platforms such as Internet Relay Chat (IRC) or Skype Groups. Everything in subreddits has been contributed by users, as links to pages elsewhere online, as original content (‘self-posts’) or as comments to linked material, to original content or to other comments. Posts and comments can be either upvoted or downvoted, and the resulting score, known as the ‘points’, affects the ordering of posts and comments and thus their visibility. As a contribution gains points, it increases in visibility by moving to the top of the page, whereas downvotes eventually make a contribution invisible. In order to post or vote on existing subreddits or construct one’s own subreddit, the visitor must register as a user (a ‘redditor’), an anonymous entity that is not tied to a real-life person (as opposed to, say, Facebook) but that carries a posting history (as opposed to traditional message boards such as www.4chan.com). The redditor accumulates positive upvotes in the form of what is known as ‘karma’, a number depicting the difference between negative and positive votes from other users over time. In that way the platform adds social value to processes of upvoting; the more the karma, the more the social value. Each subreddit has the structural resemblance of a forum or message board, and posts come in three types: an initial post, comments to the initial post, known as ‘parents’, and finally comments to parent posts, called ‘children’, that may foster children of their own. This bring us to part (b) of this section, the questions of how the platform on a general level is metricized. Numbers and metrics permeate the platform. Drawing on Power’s distinctions (Power 2004, 771) between

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first- and second-order measurements, the first-order measurements of a post in a subreddit amount to four, and they are always visible: an automatically applied and static timestamp, a dynamically adjusted point score (measuring how users upvote or downvote the post), a dynamic account of comments to the post and a dynamic assessment in percentages of the degree to which a post has been upvoted. In addition to this, hovering over the name of the poster shows information about the redditor who posted, which includes numbers on the date of joining and the ‘karma’ of the redditor. These first-order measurements, or what we refer to as the interface metrics, feed into second-order measurements or algorithmic metrics and are key-elements in organizing the distribution of visibility on the platform. The algorithmic ordering on reddit is to a degree visible, and while not completely transparent to the user, the ordering of posts comes with choices in that the user may pick between five different ways of ordering: ‘New’ is based solely on the timestamp and sorts comments to a post based on their time of posting; ‘Top’ is based solely on the points of the comment, showing comments with the highest numbers of upvotes first; ‘Hot’ and ‘Rising’ are two different ways of combining the time of posting with the numbers of upvotes and numbers of comments and ‘Controversial’ gives priority to posts with the largest numbers of upvotes and downvotes. Each of these algorithms is then further controlled by the user’s choice of time frame, ranging from ‘Past 24 Hours’ to ‘Of All Time’. The default algorithmic setting is ‘Hot’ and ‘Past 24 hours’, meaning most users view the most upvoted and commented-upon posts from the last 24  hours. These numerically coded affordances of the platform are hugely important when considering the type of social and semiotic interactions, including forms of storytelling that the reddit interface invites. Arriving at part (c) of this section, we believe three such affordances are particularly consequential: the subreddit as an individual entity, the point score and the anonymity of users. We will consider them in turn. A subreddit’s combination of specific moderators, specific rules and sets of norms, values and notions of what counts as relevant and what does not, cultivated through thousands, even millions of upvotes and downvotes over time, all feeds into dynamic formations of trans-individual and semi-autonomous communicative environments, generating and negotiating values and identity through the continuous measurements made possible by the voting mechanism. This autonomous character of subreddits is a distinctive feature of the platform. Massanari stresses how the most striking feature of reddit’s ecology is its ‘contradictory nature’ (2015,

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15), which follows from the fact that so many and such different subreddits, each conforming to its own rules and norms, exist side by side. As a platform, reddit is fraught with fundamental tensions and dilemmas. On the one hand, as Massanari finds, the platform enables anyone to have their own say about almost any topic, which in principle would lead to making the site as a whole express all possible takes on all possible topics. On the other hand, the individual user tends to seek out a very limited number of subreddits that mirror his or her existing interests and inclinations. Following from this, Massanari states that ‘reddit is both one and many cultures’ (2015, 14) and shows that even if different subreddits may hold diametrically opposed ideas, the outlook and mood of reddit postings is both altruistic and cynical, both playful and serious, both out to get those abusing power and going after weak persons. The second affordance of particular importance, the point score, is a key interface metric as well as a key algorithmic metric on the platform. In order to describe how interactions on the platform revolve around it, a comparison with the Like function of the more thoroughly researched Facebook platform may be helpful. In some respects, reddit’s upvoting and downvoting mechanism, which produces the point score, works as a slightly more transparent version of the original Like button on Facebook. Gerlitz and Helmond have argued that the Like button holds a double role with its ‘capacity to instantly metrify and intensify user affects—turning them into numbers on the Like counter—while fostering further user engagement’ (2013, 1349). By pushing Facebook’s ‘Like’, a user’s engagement is measured and visualized through the increased Like count and furthered through the creation of value, or as Gerlitz and Helmond put it: ‘data and numbers have performative and productive capacities’ (1360). This double mechanism of expressing and creating value is also crucial to what the point score does on reddit. Upvoting a post makes it more visible and thus creates value, and it is the simplicity and efficacy of this value production that has made reddit continue to grow as a platform. Thanks to what (initially, at least) was a radically democratic system where anyone could join but no one could know who you are or how you vote, the posts found by most users to hold the most value have tended to gain the most visibility, weeding out spam, junk and low-quality contributions while securing prominence to what the users of a particular subreddit find most valuable to them. The algorithm driving the default ‘Hot’ sorting does come with other consequences, however. In keeping with the overall intent towards transparency of how the platform works, the code behind

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the algorithm is available as an open source. Salihefendic (2015) has dissected the code for reddit’s post-sorting algorithm, and he shows how the visibility of posts is a factor of the relationship between, on the one hand, upvotes and downvotes and, on the other, time3: ‘Submission time is a very important parameter, generally newer stories will rank higher than older. The first 10 upvotes count as high as the next 100 […] Controversial stories that get similar amounts of upvotes and downvotes will get a low ranking compared to stories that mainly get upvotes’ (Salihefendic 2015, n.p.). This has consequences for what types of content and what type of voting has the most impact. As Mills explains, ‘Reddit’s algorithms are geared to focus the attention of a subreddit’s subscribers on a small proportion of submitted content’, which ‘makes it more suited to handling content that can be appraised and voted on very quickly’ and ‘gives an advantage to shallow content that can be easily consumed, and gives power to users who make shallow decisions’ (Mills 2018, 51, 53). This poses potential threats to equating visibility with quality. It also risks rendering certain forms of posting and voting more likely to have an impact than others: ‘For as long as votes are unlimited and anonymous, users who are minded to make an impact on reddit’s collective decisions can increase their influence simply by voting frequently in the right places’ (Mills 2018, 53). The third crucial affordance is the role given to users. On reddit, exchanges, interactions and, ultimately, the production of cultural value revolve around the shared interests of a group of people, rather than around individual users. The interface puts content rather than subjects at the centre of attention; the interface does not keep track of or count how a user votes in order to personalize future communication to that user and users do not have followers. The role and status of users is the feature of reddit that has given rise to most scholarly debate, with some studies focusing on the consequences of this form of anonymity and others questioning the nature of this anonymity. The two extreme positions in the first part of this debate are summarized by Kilgo et  al. as follows: ‘The combination of anonymity and online communication reduces personal accountability and can create an “online disinhibition effect” which can provoke hostile actions or troll-like behaviors […] as well as supportive behaviors’ (Kilgo et al. 2018, 2). Beginning with the supportive behaviours, several scholars have argued for the positive effects of reddit’s form of anonymity. Henninger states that for ‘medical professionals, the availability and afforded anonymity of a platform like Reddit is vital to free

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exchange that can serve multiple functions, such as social support and ethical reassurance’ (Henninger 2019, 16). Along similar lines, dealing with reddit posts about sexual abuse, Andalibi et al. show the ‘importance of context-specific anonymity in support seeking’ (Andalibi et  al. 2016, 1), while O’Neill states that ‘the anonymity of /r/rapecounseling acts as a safety net, allowing survivors to discuss their real-world vulnerabilities’ (O’Neill 2018, 49). The veil of anonymity, however, may also give rise to very different types of behaviour. In 2017, Massanari argues that reddit has become ‘a hub for anti-feminist activism’. Looking at ‘gamergate’ and ‘the fappening’—two examples of what Massanari calls ‘toxicity’ on social media that originated on reddit—she emphasizes the importance of the affordances of the platform in supporting the emergence of deliberatively destructive types of communication: ‘Reddit’s karma point system, aggregation of material across subreddits, ease of subreddit and user account creation, governance structure, and policies around offensive content implicitly encourage a pattern of what I call “toxic technocultures” to take hold and have an outsized presence on the platform’ (Massanari 2017, 330). Through default use, the platform does not offer complete anonymity, since over time it records and makes visible some of the actions that users perform. ‘Redditors begin to chip away at their anonymity the moment they create an account by leaving bits of information through interactions, posts, comments, and activity’ (Kilgo et al. 2018, 1). This trail of information is numerical, counting the karma score and the longevity of the user. These dynamic interface metrics are not trivial to the interactions on the platform. The karma score aggregates ‘social capital’, since it is ‘the form in which peer approval is manifested on the site’ (Van der Nagel 2013, 6). Kilgo et al. have shown that even if the potential importance of a redditor is not related to the number of friends or followers, it is still sometimes possible for a small part of the members of subreddits to acquire positions akin to ‘opinion-leaders […] by establishing their reputation through karma’ (Kilgo et al. 2016). How, then, does the particular design of the reddit platform influence storytelling practices? As should be expected, something as diverse as more than 130,000 individually moderated subreddits may lead to a multitude of narrative forms and practices, making it impossible to answer the above question comprehensively. Our aim here is, therefore, more modest in that we want to investigate how a specific public, directed towards political issues, develops narrative strategies that not only fit the platform and

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its metricized affordances but may be said to form a kind of symbiosis with it. Recalling Marie-Laure Ryan’s statement that ‘when it comes to narrative abilities, media are not equally gifted; some are born storytellers, others suffer from serious handicaps’ (Ryan 2006, 4), it is worth noting that a similar case can be made for digitally networked platforms in that different sets of affordances entice different types of communicative interactions. Many of the platforms that revolve around a user profile, such as Facebook and Instagram, can be said to be narrative by design, because of their reliance on the evolving identity and life history of a person; on such platforms, autobiographical, even if highly interactional and recency-­oriented, forms of storytelling emerge naturally, as has been investigated in Page’s work on microblogging and second stories (Page 2012, 2018) and in Georgakopoulou’s work on narrative stance-taking in relation to Facebook status updates (2013). The design of reddit, as we have argued above, due to its focus on exchanges of opinions, meanings, guidance and sharing of and debate about the state of facts rather than on unfolding lives, makes the platform a less natural arena for storytelling. We do not mean to argue that autobiographical narratives play no role on the platform, because obviously they do and examples are omnipresent; from personal stories used in debates about motivating weight loss in r/loseit to the highly popular IAmA format where real-life people, either public figures or persons with unconventional experiences, tell about their lives in a crowdsourced, live interview. What we argue instead is that the design of the platform invites certain types of interaction and behaviour. As we will show, its signature combination of interface metrics and algorithmic metrics rewards certain forms of narrative practices, including processes of memetic rescripting and reflexive narrative practices that are primarily about how platformed metrics produce visibility.

3.3   Methods and Material To reiterate, subreddits and the processes of cultural meaning-making they are home to come in very different shapes and sizes, even as they operate on the basis of the same affordances and materialize through the same interface. One of the challenges in addressing storytelling practices on the TD subreddit, our object of study in what follows, is to define or even describe just what this material is. This challenge of grasping TD as a

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certain kind of cultural artefact is not only a terminological one. A keycharacteristic of TD lies in its subversive positioning towards established forms of community building and movement organization. Because of this intimate link between what the subreddit does and what it is, we will now, in some depth, prior to explaining our choice of method, discuss how to characterize TD in relation to ideas about online community, counterpublic and online crowd. TD was established in 2015, as Donald Trump started his run to become candidate for the presidential election in 2016. From early 2016, following Trump’s rise, it saw a steady and massive influx of new members. Early on, it produced both actions and content that pushed even the free speech ethos of reddit to, and sometimes beyond, its limits, leading to several temporary warnings and bans. It describes itself as ‘a neverending rally dedicated to the 45th President of the United States, Donald J. Trump’. The content during its meteoric rise in the first half of 2016 consisted of 25% self-posts and 75% posts linked to other places online. Of these, YouTube accounted for 14% and picture-sharing sites imgur. com and Sli.mg for 29%, and www.breitbart.com was the most linked-to website (Mills 2018, 48—based on an analysis of the 270,000 posts and 2.7 million comments that appeared in the subreddit from February to June 2016). The organizational formalization of the subreddit and its users is unclear. Despite the fact that Trump has posted multiple times on the subreddit and that material from TD has found its way into the communication flow from the Trump staff both prior to and during his presidency (cf. Lagorio-Chafkin 2018, 387), no official links exist between TD and the Trump campaign or administration. Another set of informal overlaps exist between part of the content, the members and the moderators of the subreddit and what is being referred to as the altright or far-right movement.4 It is this overlap with themes, issues and calls to action, typically connected to alt-right rhetoric, that from the beginning earned TD its reputation. As Lagorio-Chafkin puts it: ‘by mid-2016, The_Donald had become a two-hundred-thousand-strong community producing a steady stream of far-right talking points, coded racism, casual misogyny, Islamophobia, and the now-well-established alt-right “free speech” and hatred of the mainstream media’ (LagorioChafkin 2018, 385). Lagorio-Chafkin refers to TD as a ‘community’, a term that may serve as a starting point for reflecting on what TD is.5 Panek et al. defines an online

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community as ‘a group in which most members contribute equally to a discourse (i.e., participation is widely dispersed among group members) and one in which active participation is sustained for a prolonged period of time’ (Panek et  al. 2018, 2). TD and the activities taking place on the subreddit seem to match these descriptions: many members interact with each other and contribute to a persistent accumulation of discourse through the interface of one delimited subreddit. But, as will become evident as soon as we dive into the quantified practices that emerge from these interactions, TD also exhibits behaviour typically aligned with other forms of trans-individual activity. Mills describes TD as ‘a subaltern counterpublic’ (Mills 2018, 52), drawing on Fraser’s classic notion of counterpublic (Fraser 1990). Fraser’s notion of counterpublic is elaborated on by Warner, an elaboration that emphasizes why it matters beyond nomenclature whether TD is approached as a community or a public. It also helps us better understand what is at stake in the narrative practices in TD. To Warner, a public is a ‘self-organized […] relation among strangers’ existing in a ‘social space created by the reflexive circulation of discourse’, whose address ‘is both personal and impersonal’ (Warner 2002, 54–66). A public differs from a community or group, because the sum of its participants can never be fully known, because it exists through the ongoing address of the discourses that it circulates and because this circulation continuously ‘promises to address anybody’ (81). The circulating texts of a public address not any specific individual but an indefinite number of persons, and anyone may enter a public by paying attention to its discourses. Publics rely on the discourse they make possible, to the degree that Warner calls them ‘world-making’, adding that this world-making happens as much through ‘affect and expressivity’ (83) as through traditional conversational means. Warner’s elaboration on Fraser’s thinking on subaltern counterpublics skips the term ‘subaltern’ because it limits the types of publics that can be considered to be ‘counter’. Warner sees three factors as differentiating a counterpublic from a normal public: it exhibits ‘an awareness of its subordinate status’ (86); the ‘discourse that constitutes it is not merely a different or alternative idiom, but one that in other contexts would be regarded with hostility or with a sense of indecorousness’ (86); and it offers a different level of identity-forming potential to its members, in that ‘addressees are socially marked by their participation in this kind of discourse’ (86). Where publics ‘unite strangers through participation alone’ (56), ‘counterpublic discourse also addresses those strangers as being not just anybody’ (87); ‘participation in such a public is one of the

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ways its members’ identities are formed and transformed’ (87). These three features of the counter-discourse are, as we shall see, key to what transpires on TD. Research on online communities and publics has traditionally not focused much on the affective and emotional dimensions of these social formations. In a series of publications, Papacharissi and others have addressed this gap through analyses of trending, politically motivated hashtags on Twitter and by elaborating on boyd’s idea of a networked public by suggesting the term ‘affective publics’ (Papacharissi 2014, 2015; Papacharissi and Blasiola 2017). The idea, which draws on Warner’s notion of publics as self-organized, is that ‘the form of content streams […] is affective in nature […] and these streams serve to discursively call in to being public formations, that I refer to as affective publics’ (Papacharissi 2015, 4). What is particularly interesting in this work, even as it looks mainly at explicitly political movements, is that it offers a take on what roles narrative may play in these kinds of collective situations. According to Papacharissi, affective publics ‘serve as storytelling structures that sustain a modality of engagement that is primarily affective’ (Papacharissi 2015, 4). Social media allow for movements or publics to, as Papacharissi and Blasiola put it, ‘frame their story in their own terms […] they permit each individual involved, affiliated, or interested in a movement to become a storyteller, contributing to the collaborative narrative woven online and offline about the movement itself’ (Papacharissi and Blasiola 2017, 211). This idea of seeing storytelling as part of what weaves a movement, or public, together (even if Papacharissi does not got into specifics as to what amounts to storytelling and what does not) is also helpful for understanding the practices developed on TD. During particularly heated moments, affective publics could be said to turn into an online crowd, which Stage, drawing on early sociological theories of Le Bon and Tarde, has characterized as a ‘way of being together in which the personal dispositions and rationality of the individual are subsumed under the unpredictable energy of the collective mind […] the crowd works according to a logic of contagion and suggestibility’ (Stage 2013, 2). Stage distinguishes between three types of crowds: the traditional ‘body-to-body crowd’ of physical co-presence, the ‘mediated crowd’ that combines offline and online presences and ‘the online crowd’. The latter designates ‘a certain type of online behavior where the participants of a public simultaneously (1) share affective processes and (2) come together on certain online sites’, displaying ‘affective unification and

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relative synchronization’ (Stage 2013, 6). The affective traces materialize in certain types of content (‘the representational content of the posts and comments’), in discursive anomalies (‘the form of the comments (e.g. if discourse is distorted, ruptured, or redundant’) and around specific events (‘in temporally simultaneous gatherings around specific blog posts in relation to certain dramatic events’) (Stage 2013, 8). Compared to online communities and to publics/counterpublics, online crowds are thus more ephemeral and spectacular in nature, erupting and causing eruptions (often possible to identify through sudden rises of interface metrics and upvoting scores), typically over shorter periods of time and around specific events, and dominated by high and hectic emotional and semiotic intensity. So is TD an online community, an affective (counter)public or an online crowd? We want to argue that it is somewhat a mixture of all three. Operating, at the outset at least, from inside the confines of one shared space and consisting of members, the community aspects of the subreddit are challenged by the obvious intent to create, through circulating hostile and indecorous discourse, a counterpublic that is open to strangers and aimed at other publics, including that of the political state. This takes place in a process which is continuously interspersed with moments of intensified and affect-laden behaviour. The subreddit is thus a community to the extent that some of its members seem to engage in sustained interaction based on somewhat shared political values; it is an affective counterpublic because the overall political agenda of the subreddit is to affectively engage followers and to promote specific, previously marginalized political views in the larger American (or even global) public sphere; it is an online crowd if we zoom in on more demarcated peaks of affective unification taking place in relation to specific texts and events during the flow of communication in the subreddit; and it is, first and foremost, a mediated public consisting of strangers paying attention in various ways to the same circulated texts, if we focus on the entire group of potentially very heterogenic members of the subreddit (cf. 800,000 people incl. lurkers, opponents, cultural consumers, etc.). Such a description rhymes with TD’s own characterization, the idea of a ‘never-ending rally’—a description that hides important differences while highlighting key similarities between the physical gathering of an audience at a traditional political rally and the online-only, persistent interactional practices of this subreddit. Like a traditional political rally, TD aims for strength in numbers by bringing together a group—the bigger the better—of enthusiastic, one-sided supporters in a somewhat

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delineated setting that encourages coordinated energetic outbursts such as applause, cheering and laughter, all directed at shared ideas uttered by speakers. Unlike a traditional rally, TD is unaffected by physical constraints such as time and space, its utterances have material permanence and they may originate from potentially everyone who chooses to be addressed by and take part in the production and circulation of the discourse that makes up this particular view of the world. This discussion of what TD is carries weight when trying to understand how its practices of quantified storytelling emerge and function. We will return to it in more detail later. Prior to zooming in on how platformed rallying is intertwined with numbers and narrating (and vice versa) on TD, some words on our method and choice of material. As should be evident, the fragmented, dynamic nature of any subreddit, let alone TD, makes it a challenge to approach as someone wanting to analyse it. The methodological setup chosen here consists of a combination of what Squirrell calls ‘lurking ethnography’ and rhetorical close reading. Lurking ethnography, deployed by Squirrell in an analysis of moderators on reddit, equates ‘(observing and reading the subreddit without commenting or posting) to gain an understanding of community norms’ (Squirrell 2019, 1914). This extensive lurking—in our case the daily reading of posts and comments on TD from early 2016 through to mid-2017—may then, as it does in Squirrell’s case, be supplemented with qualitative interviews. We will instead be combining it with rhetorical close reading (Jasinski 2001; Browne 2009), an approach to texts in contexts that assumes texts possess ‘“a rhetorical texture” […], they embody a certain “integrity and density” […], they are a site of “action” (p. 378), and they are constituted by an “internal dynamic”’ (Jasinski 2001, 92). The text chosen is the post ‘Trump: As president, I would prosecute Clinton’ (redd.it/476jze)6 and the comments it generated. It was created on TD on February 23, 2016. We have picked this post and its comments because we find it to be both a ‘paradigmatic case’ and an ‘extreme case’ (Flyvbjerg 2006, 233) of how quantified storytelling and platformed rallying interact on TD. It is both ‘prototypical’ and ‘especially dramatic’ in that it displays features shared by most posts during this period while also radicalizing these features by taking them to their extremes. The paradigmatic and extreme nature of the post and its comments is further enhanced by its appearance at a crucial time in the development of TD. As evident by the statistics provided by www.subredditstats.com/r/the_donald, TD has shown a remarkable ability to keep growing since its inception in

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2015. It reached 100,000 subscribers in April 2016, 200,000 in August 2016, 300,000  in November 2016, 400,000  in May 2017, 500,000  in September 2017, 600,000 in April 2018 and 700,000 in January 2019 This particular post and the discussion it created stems from the time frame where the rate of attracting new subscribers was much higher than the average climb of this curve: one week of February 2016, during which the number of members more than doubled (from 20,000 to 45,000). This accelerated influx of new members to the community correlates with storytelling practices aimed at taking advantage of the metricized affordances of the platform. It also correlates with a high level of discursive reflexivity in the subreddit regarding the identity of this particular gathering and regarding the ways it may prosper. It further correlates with a period of time where the subreddit most successfully managed to spill over from its own borders into the shared r/all page of reddit, potentially reaching a much wider readership. Mills’ work on the data of this period finds that 59 posts appeared on /r/all in February 2016 (Mills 2018, 48). The post amassed 12,300 points, making it by far the highest upvoted post and the fifth most commented-upon post during the more than doubling of the community that took place between February 20, 2016, and February 29, 2016 (Table 3.1). Of its 217 parent comments, 39 have negative points (below −50 and 0), totalling only 100 children, while 31 have more than 50 positive points (from 50 to 1800), totalling close to 1100 children. In other words, most of the engagement in this, the most engaged thread during this period of high engagement, centres around fairly few upvoted parent posts. The top 31 parent posts and their 1100 children can therefore be considered representative of the thread as a whole. Neither the thread itself nor everything that unfolds in it can be said to be narrative in the sense defined by Walsh (see Chap. 1). As with most cases of storytelling in rhetorical discourse (Iversen 2014, 2017), fully developed narratives are far between, but plenty of small story activity takes place, in fragmented and dispersed forms. We will identify two storytelling practices, both intertwinement with the metric facilities of the platform, through a reading of what we take to be the three main themes dominating this thread, as well as the subreddit as a whole. All three themes are clearly visible in the two comments with the highest point score. The highest voted parent (1800 points) simply says ‘Meme magic’ (Fiilu 2016) and links to a screenshot from a 4chan message board. The top-voted child of this parent, itself at 1500 points, holding a massive 371 children, begins: ‘Also since this is on /r/all, I would like to take a quick

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Table 3.1  Number of upvotes and comments on the ten most commented-upon posts on r/The_Donald from February 20, 2016, to February 29, 2016 Thread title

Number of upvotes

redd.it/47m5sj: “Texas GOP Debate—Discussion Thread” redd.it/46stse: “DONALD TRUMP WINS SOUTH CAROLINA!!!!” redd.it/479mk9: “Nevada Caucus—Discussion Thread” redd.it/47aymb: “TRUMP WINS NEVADA!! CENTIPEDE REDDIT!!! THIS TIME WITH MORE P!!!!” redd.it/476jze: “Trump: As president, I would prosecute Clinton” redd.it/47q8gk: “NJ Governor Chris Christie endorses Donald Trump for president” redd.it/486blq: “LIVE Stream: Donald Trump Rally in Madison, AL (2-28-16) [RSBN]” redd.it/47bdx7: “To everyone complaining about Donald invading /r/all…” redd.it/46sou9: “South Carolina Primary Discussion Thread with Live Results Link” redd.it/47uzap: “Bernie supporters stealing Trump signs. They don’t just brigade online.”

Number of comments

1000

10,358

4100

3255

1300 2900

3218 2073

12,300

1541

5000

1123

707

1057

5500

976

672

970

2500

952

moment to educate the incoming redditors who may not know about what Trump stands for’ (AngryRedditorsBelow 2016) before offering a long list of information on the political platform behind the Trump campaign. These two comments are emblematic of what we identify as three distinctive themes in the thread; we will refer to them as meta-memetics (‘Meme magic’), political education (‘educate’) and outreach and influx (‘This is on r/all’), concerned with, respectively, the form, the content and the audience of this particular form of platformed rallying.

3.4   Analysis Meta-memetics The first theme, what we call ‘meta-memetics’, describes what many would consider to be the dominant feature of the interaction that unfolds on TD: its peculiar, yet immediately recognizable rhetorical style. The first

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comment on the thread, posted 30 seconds after the initial post went live, may serve as an example: ‘Dammit it all I came here to post his... YOU HIGH ENERGY NIMBLE NAVIGATING KARMA THIEF!!!!!!!!! Imma build a wall around your face! 9 coats for you!!!’ (MorePancakes 2016). While clearly investing linguistic markers of affect (using swear words, hurried/sloppy spelling, typing mistakes, multiple exclamations marks and caps lock), it is less clear what the poster is investing the affect in. Not in itself a fully formed narrative, the idea of calling someone a ‘nimble navigator’ as well as the wish to ‘build a wall’ and to give ‘coats’ only makes sense when read as quotes or remixes of references to existing narratives, all involving mediatized and controversial utterances made by Donald Trump. The post reads like a mosaic of quoted fragments from media stories. ‘High energy’ repurposes a repeated formulation used by Trump to denigrate his opponent Jeb Bush during the 2015 parts of the campaign: ‘He’s doing very poorly in the polls, he’s a very low-energy kind of guy, and he had to do something’ (ABC’s ‘Good Morning America’, September 2, 2015). ‘Nimble Navigating’ quotes the song ‘Centipede’ by dubstep act Knife Party, which opens with a quote from a nature documentary describing the centipede’s ability to use ‘nimble navigating’ and poison to kill way larger bugs and insects. This song featured as a soundtrack on some of the more than 30 YouTube videos in a series called ‘You can’t stump the Trump’ showing Trump dismiss or negate political opponents, effectively equating the bug’s surprising lethality with Trump’s unconventional political and rhetorical manoeuvres. ‘Build a wall’ references a key-component of Trump’s political program, the intent to build a wall in order to keep illegal immigrants from entering the United States. ‘9 coats’ refers to a statement Trump made at a January 2016 rally. As supporters of Bernie Sanders began to chant against Trump, he ordered to have them thrown ‘out into the cold’, adding ‘Don’t give them their coats […] No coats! Confiscate their coats’.7 As becomes evident when trying to explicate these discursive fragments, they draw their meaning from narratives about Trump which at the time were widely circulating, not least in mainstream media. While this comment’s particular combination of ‘high energy’, ‘nimble navigating/centipede’, ‘build a wall’ and ‘coats’ is unique, the use of precisely these discursive fragments is highly typical for this thread and for TD in general. These fragments, and a few others, including ‘cuck’ and ‘stump’, are massively over-represented throughout the postings made by the community during the first half of 2016 (Mills

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2018). In this thread alone, they appear in numerous constellations, many of which tell hypothetical stories of future events. One, gaining 122 points, constructs the following scenario about Hillary Clinton: ‘Trump will stump the shit out of her. She will never ever try to play that low energy woman bullshit ever again. He will take her coat and build a wall of HIGH ENERGY’ (dakkottadavviss 2016). Another, which gathers 807 points and 73 children, uses the phrases as part of an elaborate fictionalized8 narrative about Trump’s 2017 State of the Union address where Trump, aided by Chris Christie, wards off a potential assassin. The following quote is a short excerpt of the full story: “AT YOUR STARBOARD, MY LEIGE!” Bellows Christie, pieces of donut spraying from his beautiful mouth all over the hair of one of the concubines the Donald rewarded him with, for his sacrifice. As quick as lightning, before even the Secret Service can react, the centipede draws two cold, hardened pistols from his cc holsters. This centipede is a predator. The cuck never knew what hit him. Twin Glocks unload 34 rounds of hot lead in to his skull. I repeat, this centipede is a predator. (HonoredPeoples 2016)

This practice of speaking and storytelling with selected quotes from circulating cultural artefacts can be seen as an advanced or accelerated form of what Shifman calls the ‘hypermemetic logic’ (2014, 32) of digitized, networks-based communication. Shifman defines memes as ‘(a) a group of digital items sharing common characteristics of content, form, and/or stance, which (b) were created with awareness of each other, and (c) were circulated, imitated, and/or transformed via the Internet by many users’ (41). Following Knobel and Lankshear (2007), Shifman sees the power and aesthetic characteristics of memes as relying on and producing ‘forms of incongruity’; a meme ‘creates a dissonance, a puzzle that users may feel inclined to solve or further highlight by creating their own versions’ (2014, 80). Memes come to life through ‘anomalous juxtapositions’ and are ‘deliberately provocative’ (Knobel and Lankshear 2007, 215), making their exact meaning and thus their functions difficult to pin down. Phillips and Milner use the term ‘ambivalence’ (Phillips and Milner 2017) to describe the unwieldy semantic and rhetorical effects of processes of memetic interaction. What characterizes the rhetorical style of TD is that rather than merely referencing to memes, showing memes or discussing memes (even if all three things do take place), the communication itself appears to be meme-ified. Those taking part in the public’s

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circulation of discourse are speaking through the memetic fragments, hence our description of this as a meta-memetic practice. Lagorio-Chafkin describes the effects of this as a creation of ‘symbols that were individually absurd, but collectively as poignant to their audience as was the Obama “Hope” poster eight years earlier’ (2018, 386). The practice is simultaneously dead serious and deeply ironic; its hypostatization of the most extreme and indecorous traits of Trump’s rhetoric and persona simultaneously makes fun of and underlines the importance of taking actual consequences of the shock to the political system, which Trump’s candidacy promises. It is simultaneously radically playful and indicative of the constitution of a shared identity. Seen as a form of narrative practice, we would call this incongruous rescripting. The term ‘rescripting’ has been suggested by Georgakopoulou (2014). Georgakopoulou and Giaxoglou describe it as follows: ‘Rescripting routinely entails the creation of humorous, satirical takes on an incident […] It also involves manipulations of plot ingredients so as to create more or less cryptic analogies between an “original” incident and other already circulated stories’ (2018, 3). The process of rescripting differs from the creation of digital memes because (1) the former always entails sequential linear temporality/plotting, while the latter does not and (2) the latter always entails incongruousness while the former does not. TD’s ability to rescript existing stories is evident in how it deals with a key-case of content metrics in the context of political rhetoric. A substantial part of the storytelling on subreddits related to political candidates is concerned with numbers. One of the prototypical narrative formats on such subreddits is a small story about how and often why the poster has donated a certain amount to the campaign in question. A case in point is the subreddit r/sandersforpresident, which in February 2016 was one of the biggest subreddits with more than 150,000 members and which was filled with posts of this kind. The TD subreddit offers incongruous rescriptions of this format; a top-voted parent comment (1014 points) reads: ‘Whoa! This calls for a donation, methinks! Just donated $0000.00, MATCH ME, DOUBLE ME, QUADRUPLE ME BROS’ ([deleted1] 2016), which initiates a string of children posts, echoing and further radicalizing the rescripting process: A 311 points child posts adds ‘$0000000000000000.00000000 DONE!’ (VonIssendorff 2016), while another 175 points child post adds ‘THIS MIGHT SET ME BACK BUT…. AH FUCK IT ANYTHING FOR THE DONALD $0.00 DONATION’ (leredditxddd 2016). These fictionalized rescriptings may be parodies of the sincere, pathos-laden, self-congratulatory and

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sacrificial vocabulary, characteristic of the traditional donate narrative, but while they make fun of one type of metric accumulation (money), they are themselves invested in another type of metric accumulation. Their goal is to attract upvotes, which secures visibility. What they also show is the subreddit’s ability to construct and harness, as well as mock the mechanisms, driving what Stage calls online crowds. The excessive use of linguist markers of surprise and wonder, such as the use of bold typeface, caps lock, exclamation marks and swearing, conjures forth expectations of an ongoing or forthcoming ‘affective unification’ (Stage 2013, 6). The incongruous vocabulary works as a provocative set of building blocks, as a do-it-yourself kit for producing outrageous types of texts, many of which are fictionalized narratives. The recurring blocks and phrases in this one thread correlate with Mills’ findings from a large dataset. He ‘collected the 500 most visible comments for each of these 59 posts that appeared on /r/all in February, a total of 18,008 comments’, and he highlights the following as the most recurring phrases: ‘“HIGH ENERGY”, “cucks”, “centipedes” and “nimble navigators”, “berniebots”, “MAGA”, “Donated $0.00”’ (Mills 2018, 48). The vocabulary is closely tied to the affordances of the platform. Thanks to the anonymous and easy user creation process and the already existing vocabulary of the subreddit, the barrier of entry is low, while the metrics of the voting system ensure that the most eye-catching contributions gain high visibility, thus enticing members to come up with creative and entertaining rescriptions. The vocabulary is an accelerated and reflexive case of what Warner calls the reflexive circulation of discourse, constitutive of a public. Text and fragments of text are reused time and again in a continuous stream of affectively laden outbursts, not really beginning and not really ending. This rhetoric of TD evidently, and always with an ambivalent twist, displays the features central to the discourses of counterpublics: it differentiates itself from dominant public discourses through excessive indecorousness by its use of inappropriate content (often bordering on racism, misogyny and hate speech) and by its use of inappropriate form (from swearing to in-group expressions to non-conforming syntactic and typographic choices). It thematizes, flaunts even, the unfitting status of its members, by equating them with highly energetic bugs, thus leveraging the identity-forming potential of a counterpublic. It may be tempting to file this practice of meta-memeticism under playfulness and to see the semiotic and narrative experiments as forming a closed system, feeding on its own internal logics, sealed off from the rest

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of the world, akin to what Squires would call a ‘satellite counterpublic’ driven by the ‘desire to be separate from other publics’ (Squires 2002, 463). Such an understanding would, however, be missing a crucial point. This counterpublic does not see its incongruous, meta-memetic practices as being opposed to engaging with reality, but rather as shortcuts to real life. This is what is alluded to by the top-voted parent post ‘Meme Magic’. It links to a screenshot from the anonymous 4chan website, dated February 2, 2016, more than three weeks prior to the initial post. The screenshot shows two posts, the first saying: ‘I absolutely cannot wait until Trump turns all his savagery on Shillary during a nationally televised debate’, the second replies with a fictionalized story of how Clinton gets arrested by FBI on live television while Trump utters ‘you’re fired’.9 Taking part in TD’s crowd, either by voting or by posting, means taking part in meme magic happening: the story referred to in the head post of the thread— Trump asserting that as president he would prosecute Clinton—is real-life politics conjured up by means of a fictionalized narrative. Even if these meta-memetic practices are the most striking part of the thread and the community as a whole, they only take up approximately half of the 31 parent posts with more than 50 upvotes. Political Education When we now turn to the second major theme in the thread, what we have referred to as the theme of ‘political education’, it becomes evident that quite of lot of the most popular comments aim at getting an actual message across. At least seven of the top parent comments (totalling more than 600 children) are invested in trying to ‘educate’ redditors about the political platform Trump is running on. Under the heading ‘This is what Trump’s platform is’, a 1500-point comment lists Trump’s take on 19 cores issues such as foreign policy, taxes, health care, social issues, trade, diversity and immigration, ending with an equally traditional ethos push: Trump has ‘created tens of thousands of jobs just with his own personal business, imagine what he could do by being a leader of America’ (AngryRedditorsBelow 2016). Through most of the 370 children to the comment, commenters engage in what amounts to a typical online political debate. The main thrust behind the most upvoted of these posts is to go counter to what is presented as erroneous narratives about Trump as a person and his campaign, propagated by the established media outlets. One post with 106 points states that ‘The media has tried to push the

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narrative of “xenophobe, racist, sexist, islamaphobe, etc.” but when they actually interview anyone that’s ever been in contact with Donald Trump they all say the same thing, the man is not a racist’ (oldie101 2016). Posts dealing with this theme talk less in narratives and more about narratives, trying to ‘end the relationship with the mainstream media!’ (sweetcaviar 2016) and counter its depictions of Trump. Rather than invite members to dial up the level of affectivity by joining in on the counterpublic’s identity-­forming, incongruous rescriptings, these posts are out to dismantle stories already circulating in the media and to offer what is presented as facts: ‘A lot of newcomers will drop into this sub and just see the meme magic. High energy stuff, but we need to give people an opportunity to see how The Donald has been misrepresented by the media’ ([deleted2] 2016). Key-devices for this are lists of core ideas of Trump’s ideological platform and links to other online sources: ‘After work today I’ll gather a bunch of links to interviews/rallies/articles so we have direct evidence to back up each point about Trump’ ([deleted2] 2016); ‘Google it—tons of sources available for this fact’ (RiotGorilla 2016); and ‘If you’re willing to at least hear the other side of the story about the “outrageous” things he’s said over the last seven months, I highly recommend checking out this video’ (coats_for_sale 2016). Outreach and Influx The incongruous memeticism and its creative rescriptings of Trump-­ related narratives does constitutive work by conjuring forth a particular identity, but this address operates inside the walls, so to speak, of the subreddit itself. Similarly, the educational listings of Trump’s policies that we have just demonstrated engages commenters that are already part of the subreddit. Neither one of these two themes in themselves account for or reflect the reason that the subreddit’s platformed rally during this time frame more than doubles its amount of members. Such reflection, however, is what dominates the third main theme of the thread (and, by extension, the subreddit as a whole), the theme of what we call ‘outreach and influx’, dealing mostly with issues related not to rhetoric or message but to audience. By outreach we mean the traffic of content and ideas from TD into other subreddits, most notably the default front page at this time, r/all.10 By influx we mean the traffic of new members joining the subreddit. The theme is about the two related but different ways in which the

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subreddit’s influence may grow: either by reaching people outside the subreddit or by having outsiders become members of the subreddit. Approximately a third of the 31 highest voted as well as a large amount of child posts and minor posts are concerned with the traffic of information and people in and out of the subreddit, a concern heavily influenced by and reactive to numerical values. Two main forms of traffic are represented and narrated, and they are tightly and causally connected, yet clearly distinguishable. The first and most important has to do with the outreach or dissemination of what happens on TD. As described previously, reddit holds a small number of shared, default pages whose only content consists of links to other subreddits. The most important of these is the ‘r/all’ page which in 2016 served as the front page to most users of the site and which aggregates posts from the all subreddits. Early in 2016, the main criteria for appearing in r/all, effectively swapping the subreddit’s particular audience in the thousands for a general audience in the multiple millions—for making the discourse of the counterpublic enter a broader public (Warner 2002; Squires 2002)—was the point score of a post. The post under scrutiny here—redd.it/476jze: ‘Trump: As president, I would prosecute Clinton’—became one of the posts from TD to enter r/all, and this fact heavily influences how the thread develops: as mentioned, the second highest voted educational post begins as follows: ‘Also since this is on /r/all, I would like to take a quick moment to educate the incoming Redditor’ (AngryRedditorsBelow 2016), effectively motivating the political education with the jump from relative obscurity to maximum visibility. This particular post’s move into the mainstream is typical for what happened many times during the first half of 2016 (59 times during February alone, according to Mills’ data [Mills 2018]). As noted by Lagorio-Chafkin, a ‘reliable driver of new subscribers […] was every time some piece of content from The_Donald became popular in r/ politics […] or r/all’ (2018, 384). On February 23, the visibility on r/all gives rise to a series of small stories about content metrics, intermingled with notions of interface metrics and value or rather interface metrics as value. Some address what enables the breakthrough in the first place: ‘2,500 upvotes HIGH ENERGY’ ([deleted3] 2016); and ‘We are taking our high energy to the front page…be very afraid Clinton’. Others use the break through to hint at how Bernie Sanders supporters, who at this point in time had a very active subreddit, supporting Sanders’ run for securing the nomination of the Democratic party, might invade TD through what on reddit is known as brigading.11 Others, again, based on

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rigorous real-time monitoring of the dynamic ordering on r/all, witness what they take to be censorship, as the post appears to suddenly disappear from the shared front page. A top-voted (209 points) parent comment reads: ‘CENSORED FROM R/ALL# / ENERGY LEVELS RISING# / YOUR HATE GIVES HIM LIFE#’ ([deleted4] 2016), constructing a narrative where TD’s newfound visibility leads to hate, which leads to censorship, which leads to further growth of Trump’s fandom. These are all cases of what we call reflexive quantified storytelling. This form of narrative practice takes interface and algorithmic metrics as their main topic, effectively making the acceleration of the countable tellable. What these examples show is one of the most distinctive types of platformed storytelling on reddit where the rise of the metrics related to the thread becomes the plot of the story told; these are stories about the virality of the post and thread itself, told as it spreads, here both narrativizing and further adding to the ever-accumulating point score (Nahon and Hemsley 2013; Sampson 2012). Again, we see the tendency to turn events into spectacles, which then become small epicentres of temporary online crowds: the rhetoric becomes ‘distorted, ruptured, or redundant’ (Stage 2013, 9), signalling and further enhancing an affective surplus. Momentarily, the community gives way to affective unification around an event that consists of the discourse’s own trajectory from counterpublic to public. Outreach—the dissemination of a thread or a post—lends itself most easily to such processes of narrativization, but influx of new members may also be turned into a story. A high-voted comment states ‘WHAT THE FUCK HAPPENED? WHY DID THIS THREAD DISAPPEAR?’ (ohosometal 2016), only to have someone answer ‘it didnt tho, i came here from /r/all’ (david531990 2016). The thread holds a string of comments that tell a version of the same story of someone arriving and becoming part of the community because of the appearance on r/all: ‘Bernie supporter from /r/all here’ (Auzymundius 2016); and ‘Reading this from /r/all, this is the first time that I’d support trump. I hope every other candidate has the same response’ ([deleted5] 2016). All of these influx posts receive answers from existing members, typically using parts of the meta-memetic vocabulary: ‘You don’t know it yet, but your life just improved dramatically. Welcome to the winning team. Have a whole box full of coats’ (HeadFullOfLettuce 2016).

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3.5   Conclusion We began this chapter by claiming that three affordances of the reddit platform are crucial to approaching understandings of the forms of interactions that it fosters. When combined with the discussions of precisely what kind of collaborative space TD is, insights have emerged regarding the intermingling of metrics and practices of storytelling on this rhetorically and ideologically extreme, yet also paradigmatic, thread on this subreddit. The design of reddit into autonomous subreddits invites the creations of online communities. Such communities may morph into counterpublics by opening up their discourses to potentially anybody, by stressing what Warner (2002) calls the reflexive circulation of their discourse and by thematizing the marginalization of those addressed by that discourse. TD pursues this route in ways that not only exhibit such reflexivity but also perform it, adding yet additional layers of reflexivity. It does so by invoking, in a simultaneity of parody and celebration, affective crowd structures, marked and further enhanced by extreme typesetting, unconventional semantic constructions and inventive, inflammatory combinations of narrative fragments. Becoming part of this crowd is easy, and the social risk outside the platform of joining this circulation of extreme ideological views is almost non-existent. TD also thrives because of the second affordance of the platform, the pseudonymity of its users. The third crucial affordance is the way the point score of the platform controls visibility and distribution. As a key interface metric and a key algorithmic metric, votes lead to visibility, which leads to social value in the subreddit itself and potentially to impact outside the subreddit. This is where the storytelling practices of TD are intimately connected to the quantification that characterizes reddit as a platform. In order to exert influence and ‘frame their story in their own terms’, as Papacharissi and Blasiola describe it (2017, 211), this public of reddit develops particular practices for constructing certain narratives while deconstructing others. The incongruous rescriptings serve several functions: they amplify the indecorous and non-conventional subversive potential of existing Trump stories; they invite outrageous fictionalized remixes, meant to simultaneously entertain through provocations and to provoke through entertainment; and they dismantle existing narratives of the mainstream media; all this while establishing a counterpublic with its own rules for discursive circulation. The spectacular semiotic nature of these posts practises and summons affective engagement, creating value that is visible as numbers in

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the interface metrics. Because of the algorithmic metrics of the platform, high numbers equal high visibility, and because of the algorithmic metrics of the platform, the high numbers are what allows content from TD to become visible outside the subreddit. The success of this process then becomes the content of further posts in TD, effectively constructing feedback loops of ever more energetic interactions among the subreddit’s members and thus potentially attracting new members. The metricization of these engagements turns the numerical values of the point score into attention capital—literally by making its memes count—in that it buys the subreddit entry into the mainstream and attracts supporters, boosting the number of attendees at the platformed rally. These measurable successes then feed into quantified storytelling in the form of the telling of stories about this very process, about the viral potential and breakthrough of the numbers, generated by their rhetoric. As the meteoric rise in the number of members during these few days in February 2016 show, this combination makes for a highly effective recruitment tool, as new members can easily engage in the rally through low-barrier and ‘easy-to-personalize’ action frames (e.g. content-sharing through rescriptings), as opposed to high-barrier forms of access to traditional political organizations (e.g. paid membership) (Bennett and Segerberg 2012, 745). Even if it might be possible to designate how much of the meteoric rise of TD is attributable to its communicative practices and how much stems from others factors (such as Trump’s unlikely but increasingly undeniable success in the primaries during the first half of 2016 or a wider surge of interest in alt-right-related online activities), such an endeavour would lie beyond the grasp of this chapter. Other questions regarding the attested intermingling of narrative practices with the metricization of the reddit platform have to do with intentionality and identity. Mills argues that ‘the behavior of these subreddit communities can only be understood as a collective of submitting, commenting, voting and moderating participants’ (Mills 2018, 39). Under what circumstances does it make sense to ask who or what this collective consists of? Lagorio-Chafkin offers some pointers. Based on interviews with former moderators of TD and former admins of reddit, Lagorio-Chafkin documents how what to most would seem like a frantic chaos of semiotic serendipity and memetic haphazardness is largely by design. TD is in fact heavily moderated: for instance, the thread analysed in this chapter contains a substantial amount of deletions, performed by moderators. In 2016, the subreddit’s more than 30 moderators followed what a member of reddit’s community team described as

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a ‘bureaucratic’ and ‘coordinated’ hierarchical system: ‘When a post from T-D rocketed to the top of r/all, often it was the intentional result of an orchestrated campaign’ (Lagorio-Chafkin 2018, 388). This is a case in point of platform affordances guiding behaviour. There are a number of signals indicating that the actual voting patterns of the members of the TD were in sync with their rhetorical strategies. Data on who votes on what are not extractable from the platform, but Salihefendic’s explanation of how the Hot algorithm works hints at the ways in which this algorithmic metric may be gamed by TD: ‘newer stories will rank higher than older’ (Salihefendic 2015, n.p.), which means that quick upvoting generates more visibility. As we have shown, point scores are the primary means to break through into broader publics; the counterpublic’s voice is heard outside the confines of the community when enough numerical value has been created. Mills speculates that specific voting patterns were developed by TD: ‘The reasons why /r/the_donald had such a strong presence on /r/all are not entirely clear, but it is possible that this was the result of a deliberate voting strategy by some members’ (Mills 2018, 46). According to Lagorio-Chafkin’s interview data, TD became more and more apt for this kind of orchestration in the period from February 2016 to May 2016. On June 16, 2016, however, the user ‘spez’, who is known to everybody on reddit as Steve Huffman, the co-founder and chief executive officer (CEO) of reddit, posted on r/announcements that the reddit platform would change the way their main algorithm allowed for threads from individual subreddits to reach the shared r/all: r/all is a reflection of what is happening online in general. It is culturally important and drives many conversations around the world. The changes we are making are to preserve this aspect of r/all—our specific goal being to prevent any one community from dominating the listing. The algorithm change is fairly simple—as a community is represented more and more often in the listing, the hotness of its posts will be increasingly lessened. This results in more variety in r/all. Many people will ask if this is related to r/ the_donald. The short answer is no. (Spez 2016)

The slightly longer answer to Huffman’s implied question, however, was a ‘yes, but’. As Huffman continued his announcement, he described how TD’s ‘attempt to dominate the conversation on Reddit at the expense of everyone else’ was ‘behavior’ that ‘hastened’ the decision to change the algorithm, thus in reverse manifesting the mutually feeding relationship

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between the metricized affordances of a digital platform and the communicative practices it gives rise to. In our concluding chapter, we will return to some of the more generalizable observations to be drawn from the reading of this particular form of community building. Prior to that we need to delve deeper into the mutually feeding relationships between platform affordances and forms of storytelling, and we will do so by once again shifting focus and empirical material: where the transition between Chaps. 2 and 3 included a move from individualized to collective storytelling, we will in the following chapter investigate how the relationships between metrics and narrative factor into the very design of specific platform features.

Notes 1. On June 26 2020, just prior to this book entering print, reddit effectively banned the subreddit in a decision that fueled massive debates both on and off the reddit platform. 2. https://www.alexa.com/siteinfo/reddit.com 3. As we show in the next chapter, time in the sense of timeliness and recency is also an integral part of the algorithm on Instagram, shaping the way in which stories are told and what types of metrics accompany their design. 4. The alt-right has been defined as a fuzzy-bordered ‘set of far-right ideologies, groups and individuals whose core belief is that “white identity” is under attack by multicultural forces using “political correctness” and “social justice” to undermine white people and “their” civilization. The Alternative Right is characterized by heavy use of social media and online memes. Alt-­righters eschew “establishment” conservatism, skew young, and embrace white ethnonationalism as a fundamental value’ (Southern Poverty Law Center. Retrieved from https://www.splcenter.org/fightinghate/extremist-files/ideology/alt-right February 10, 2018). 5. The discussions on what constitutes an online community or communities online have a history and continue to be somewhat heated. Early attempts to analyse group-scale interactions in digitally networked environments predate social media, gravitating towards the notion of ‘virtual communities’ (Rheingold 1994; Jones 1997). Jones (1997) suggested that the following four conditions must be met to qualify for what he called a virtual community: ‘(1) a minimum level of interactivity; (2) a variety of communicators; (3) a minimum level of sustained membership; and (4) a virtual common-­public-­space where a significant portion of interactive groupCMCs occur’ (Jones 1997: 6). Even as the notion of ‘virtual’ has since been contested (due to its implicit claim that digitally mediated phenom-

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ena are somehow less real than non-mediated phenomena), these requirements have since been quoted approvingly by others (Gruzd et al. 2011; Caliandro 2017). We will be drawing on Panek et al.’s narrower definition (2018), as should be evident. 6. This notation is a short-form link to a specific post on reddit. Links to comments to individual comments appear in the list of references. 7. https://thehill.com/blogs/ballot-box/presidential-races/265172trump-tells-security-to-confiscate-protesters-coats 8. Iversen and Nielsen (2017): ‘we suggest using the term “fictionality” to describe instances of communication that overtly invite the audience to consider the communicated as invented. This makes it possible to consider imaginative discourse as something not restricted to generic fiction, and as something distinct from any act of construction, as well as distinct from falsely pretending to be speaking the truth’ (122). 9. https://i.imgur.com/CoWWEmu.jpg 10. Investigations of how content from TD travels outside of reddit and into mainstream media lie beyond the borders of this book but have begun to be undertaken systematically by others. Zannettou et  al. show that ‘altright communities within 4chan and Reddit can have a surprising level of influence on Twitter’ (2017, 1). Based on 32 million posts and 390 million comments from reddit, harvested between June 2016 and February 2017, they conclude that ‘The_Donald and /pol/ are responsible for around 6% of mainstream news URLs and over 4.5% of alternative news URLs posted to Twitter that appear on all three platforms. Considering Twitter’s relative size, the impact of these fringe communities cannot be overstated’ (12). 11. ‘Brigading is the invasion of a topic, thread, or entire message board by a group of individuals who have organized themselves online with the purpose of manipulating content or its visibility’, Lagorio-Chafkin (2018, 383).

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CHAPTER 4

Curating Stories: Curating Metrics— Directives in the Design of Stories

4.1   Introducing Stories as Designed Features So far, we have seen how users’ perceptions of metrics and practices that take into account the metricization of their activities shape posts in which users choose to tell stories about themselves, specifically about living with cancer. We have also seen how the metrics affordances of a platform may be conducive both to posting specific types of stories with specific ways of tellings and to pushing some stories to prominence, making them more visible and more engaged with. In this chapter, we turn attention to the interactional and economic role of metrics as an integral part of the design and engineering of stories as a distinct feature on apps, which is explicitly offered as a facility for posting stories and is fittingly named ‘story/stories’. This latest tendency for designed stories, a true stories-designing spree, brings together several apps, from Snapchat (2014) and Instagram (2016) to Facebook (2017) and Weibo (2018). Georgakopoulou’s genealogical tracking of ego-centred apps (mainly Facebook, Instagram, Snapchat)1 combined with the analysis of users’ communicative practices have allowed her to identify three pivotal design phases in their evolution, concerning facilities for the presentation of the self through stories (Georgakopoulou 2017). The turn to designing stories as distinct features on apps constitutes the third phase, which, as we will see below, is part and parcel of a shift towards transient, live-streaming formats of sharing (cf. Abidin 2018).

© The Author(s) 2020 A. Georgakopoulou et al., Quantified Storytelling, https://doi.org/10.1007/978-3-030-48074-5_4

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In this chapter, we interrogate the role of metrics in the apps’ production of stories as features, by focusing on the hugely popular Snapchat and Instagram Stories. We specifically delve into the type of metrics that accompany the stories’ design and the types of stories, storytellers and audience engagement that are promoted by platforms as ideally suited to such metrics. The feature of Stories2 has been described as ‘a game changer’ (Cooper 2016) for Snapchat and so it was no accident that it was largely replicated by Instagram Stories. The widely spread view and, in some cases, criticism of an uncanny similarity of Instagram Stories with Snapchat Stories were addressed by the then Instagram CEO Kevin Systrom, who argued that a successful ‘format’ can be drawn on, taken ‘to a network’ where ‘your own spin on it’ can be put (cited in Constine 2016). In the short history of the rival story facilities, Instagram has outperformed Snapchat, as the number of stories posted on it has surpassed that of Snapchat Stories since 2017. As an estimate, 500 million people use Instagram Stories every day (Instagram Internal Data, January 2019, https://business.instagram. com/), more than twice the users of Snapchat Stories, and teenagers post on average four times more stories a day than any other age group. In fact, there is currently a prediction that ‘sharing with Instagram stories will surpass sharing through Feed views sometime in […] 2019’ (https:// embedsocial.com/blog/instagram-stories-analytics/).3 Stories are essentially collections of maximum 10-second on Snapchat and 7-second snaps (photos) on Instagram, 15-second videos and currently live streaming. Initially, they lasted for 24 hours and then they disappeared, but currently users can archive them or use highlights to store their favourite stories for longer. Stories as a feature acquire material, iconic and action-button dimensions. Stories come with a designated, by now familiar, icon on both apps (e.g. see https://support.snapchat.com/ en-US/a/about-stories). A colourful ring around a user’s profile picture on Instagram, to indicate that they have posted a story, is also a familiar sign to users. Users perform habitual actions to both post and engage with stories. On Instagram, they share a story by tapping ‘Your Story’ in the bottom left of their screen. They used to swipe left on the main camera screen to access their friends’ stories on Snapchat. Now they swipe right. They tap on a user’s profile to see their story. They use their smartphone for posting and viewing stories, and their viewing experience of Instagram Stories is much more immersive than anything else on the app, as they can view them

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full-screen. The ‘template’ stories provided encourage snapshots of daily life with a simple aesthetic, minimal graphics and brief language used as a caption, overlaid on the images or video, often accompanied by emojis, providing stage directions and an assessment of what is going on (see examples in https://buffer.com/library/instagram-stories). Metrics are at the heart of the design of Stories, as we will show (Sect. 4.4). They have become integrated into the tools offered for the stories, thus for the first time allowing users to track how individual aspects of their story’s content have performed. In this way, they go beyond the economy of visible interface metrics, complicating the dichotomy between visible (normally interface) and opaque (normally algorithmic) metrics in ways which separate and stratify users. Provision of increasingly sophisticated metrics for stories alongside tools to users for accessing them are arguably the biggest identifiable aspect of the ongoing evolution and updates of the design of stories. Metrics thus prove to be not just multi-­ faceted and complex but also deeply interwoven into all the stories’ engineering aspects. Their role then in the ecology of storytelling and engagement with it warrants urgent scrutiny, especially given that even research on stories as media-designed and ‘curated’ communication by apps is scarce (see Georgakopoulou’s 2019 article for a notable exception). Addressing this gap is, in our view, a prerequisite for interrogating the kinds of political, ethical and affective subjects that media apps seek to engineer in the context of an increasing quantification and measurability of their storytelling activities. Building on our aim in this book to show how this quantification ecology needs to be factored into any analysis of stories on social media, the insights of this chapter are the results of a critical, technographically informed method of tracking affordances, including metrics, offered for Stories as a feature. In addition, as we will show below, two types of complementary analyses have been carried out: A corpus-assisted analysis of what views and ideologies underpin the design and affordances offered for Snapchat and Instagram Stories. A case-study narrative analysis of how a power storyteller, Lele Pons, the Influencer with the most watched Stories according to Instagram-­ released figures, uses Stories on Instagram. These analyses show that the values underpinning the design of Stories, the affordances offered and key communicative practices in how they are

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deployed are revealing of three directives (cf. preferential conditions, prompts; see discussion below) for what kinds of stories will be told, how audiences will engage with them and how tellers will present themselves and their lives in them. These are sharing-life-in-the-moment, audience engagement as quantified viewing and authenticity in tellers’ self-­ presentation. We will show how these directives coalesce in regulating Stories, so that they render different aspects of their plot and of engagement with them measurable. In this process, metricization involves a complex inter-animation of content, interface and algorithmic metrics that results in interconnecting and essentially conflating (cf. commensurating) creative and affective processes of storytelling with quantification. In addition, the different tiers of (in)visibility of metrics, depending on the status of users, incentivize the close links of stories with advertising, privileging business and Influencers as major stakeholders on the production of stories. This has implications, we will argue, for the type of relationships encouraged between Influencers as ‘storytellers’ and their followers as ‘story recipients’.

4.2   Directives in the Design of Metricized Stories We posit directives as prompts to users for engaging in specific posting practices and relational actions. In line with social media analysts (e.g. Bucher 2018; Gillespie 2010; van Dijck 2013; van Dijck et al. 2018), we subscribe to the widely recognized idea that social media develop their architecture on the basis of ideas about who their intended users are and what they would like them to do (cf. Carlson and Lewis 2018). Interaction and sociality on social media are, in turn, programmed (i.e. engineered) and underpinned by the ‘logic’ of social media in general and of a platform in particular. Van Dijck and Poell (2013) see the social media logic as comprising norms, strategies, mechanisms and economies and as being grounded on four principles, that is programmability, popularity, connectivity and datafication. These principles are what, we argue, give directives their force. Directives—however subtle and implied—towards users become possible because they are supported by the apps’ tools, features and functionality that inherently facilitate and activate certain actions at the expense of others, weigh more and prioritize certain types of content and in this sense render specific types of posting and behaviour by users as more appropriate for achieving the highly valued status of popularity in their environments.

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The concept of directives highlights particular aspects of the broader notion of affordances. Affordance ‘refers to the range of functions and constraints that an object provides for, and places upon, structurally situated subjects’ (Davis and Chouinard 2016, 241). To avoid the tendency to use the concept of affordance in a loose or intuitive way (Evans et al. 2016), its different analytical implications can, according to Davis and Chouinard (2016), be specified by focusing on how specific technologies or designs simultaneously ‘request’, ‘demand’, ‘encourage’, ‘discourage’, ‘refuse’ and ‘allow’ particular forms of action. Requests and demands are made by technologies when they push subjects in particular directions. Facebook, for example, requests users to include a profile image, but the use of the platform is not depending on this. At the same time, Facebook demands that you create a profile by providing personal information (e.g. name) and making selections among categories (e.g. gender and age) before accessing the platform. The levels of encouraging, discouraging and refusing, instead, focus on how technologies respond to the wishes of subjects. Instagram, for example, encourages subjects with an inclination to engage in constant social interaction by, for example, integrating a Like button, and Snapchat encourages daily interaction between specific users due to, for example, the streak feature. Discouraged ‘outcomes are those that lie behind inbuilt barriers’ (Davis and Chouinard 2016, 243). Tinder, for example, discourages slow and reflexive matchmaking processes by only allowing short bios and presenting many potential matches to its users. Refusing occurs when objects deny subjects particular actions—for example, writing long and elaborate messages on Twitter. Last but not least, artefacts allow ‘by remaining indifferent to if and/or how a particular feature is used, and to what outcome’ (Davis and Chouinard 2016, 244). Snapchat, for instance, allows users to choose from various filters but is indifferent to which ones are actually chosen. The ‘directives’ explored in this chapter are primarily linked to the requesting and encouraging aspects of platform affordances by describing how these platforms push users towards particular communicative and interactional practices by means of metricized processes, but without creating actual demands or refusals. Although specifically tailored to the social media logic and affordances, as explained above, the concept of directives also finds affiliates in the sociolinguistic research on the dialectic between structural constraints in different contexts and speakers’ agentive practices, namely in Maryns and Blommaert’s term (2002) of pre-texting (also employed by Jones 2020,

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forthcoming, in relation to social media algorithms). Pre-texting (cf. pre-­ textuality) refers to a process of setting conditions and scenarios that prompt communicators to perform specific actions at the expense of others and to attach specific evaluations to these actions.4 Another productive parallel to be drawn is between directives and the concept of pre-positioning storytellers, which Georgakopoulou sees as a necessary counterpoint to studies of how storytellers position themselves and are positioned in stories (see Sect. 1.3) that have stressed the agentive and performative aspects of this process (e.g. see Bamberg and Georgakopoulou 2008; Deppermann 2015). Pre-positioning draws attention to the existence of a regulated—in this case, ‘curated’—potential for specific types of positioning being operative in specific types of stories that need to be taken into account in the analysis. Directives should not be seen as positing a deterministic use of apps and of their features. Users are not passive dupes but agentive communicators who have been shown to strategize, develop practices to counteract specific constraints,5 second-guess and tweak algorithms (e.g. Bucher 2018; Jones 2020, forthcoming), differ in their actions and preferences and as a result push an app and its features in unanticipated directions. That said, due to media affordances of amplification and scalability as well as to algorithmically designed pressures for users to be and stay popular (Bucher 2012), the potential for directives to lead to compliance on the part of users and, in turn, to specific communication practices becoming normative in the sense of widely available and highly sought after should not be underestimated. Hence, as this chapter argues, an analytic focus on what kinds of directives emerge from the specific design and affordances of stories is a necessary step towards exploring the interconnections of stories with metrics.

4.3   Material and Methods A Critical, ‘Values in Design’, Perspective This chapter follows on from Georgakopoulou’s work on small stories as contextualized social practices for the analysis of social media communication (Georgakopoulou 2013a, b, 2014).6 To explore social media communication, Georgakopoulou has brought together micro-analytical, social semiotic and online conversation analytic methods (e.g. Giles et al. 2015) with digital ethnography (Varis 2015) and a genealogical approach

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to media platforms. The latter draws on the fields of Science and Technology Studies (STS) and platform studies, which explore social media as ideologically laden spaces and socio-material actors with influence on communication (e.g. Beer 2009; Kitchin and Dodge 2011). Georgakopoulou’s work also draws on the emerging critical discourse analytic work on the significance of the apps’ discourses, especially via their CEOs and product managers, for how users are discursively constructed and what roles are projected for them (e.g. Hoffmann et al. 2016). This critical eye is combined with corpus-assisted discourse studies principles and techniques (see below), so as to uncover and make visible any hidden meanings and interconnections in the discourse of apps and their offerings for stories. In tune with a critical discourse analytic agenda, we view such opaque meanings as having the potential to promote certain stories and semiotic choices in them, making them more available than others and even normalizing them. Similarly, there is increasing recognition within social media studies that any critical analysis of them needs to incorporate a ‘values in design’ perspective (Flanagan and Nissenbaum 2014; also see Bucher 2018). How apps design their space, what affordances they offer their users and what participation means for them are not ideologically free choices (e.g. see Langlois 2013). Instead, they encapsulate values, norms and beliefs of a whole network of actors, ranging from programmers to designers, product managers and beta users (cf. Marwick 2013). This approach to digital communication thereby avoids equating participation in digital media with democratization as it ‘involves a reassessment of processes of cultural expression in the participatory media environment through a renewed attention to the often invisible networked conditions that enable them’ (Langlois 2013, 96). In addition, we accept that the industry-facing material produced by apps, especially through their product managers (e.g. blogs, launching documents about new features, how-to guides on the use of features) enter a chain of recontextualizations (e.g. in their critical reviews on online tech magazines), which is operative in creating circulating discourses about features. As in any critical discourse analysis, the idea here is not that these circulating discourses are affecting users’ practices unidirectionally and deterministically but that they, instead, create conditions for recognizability of social actions. Blommaert (2019, 5), drawing on Garfinkel (2002), recommends the concept of formatting in research on digital communication, where large numbers of users, geographically dispersed

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and unknown to one another, enter communication ‘stages’ without any prior shared history. A key way in which communication takes place in such cases is through formats, social actions which, through occurrence and repetition, become recognizable to others. Recognizability involves processes of acquisition and learning, and it ultimately leads to reflexivity on the type and value of a format. Circulating discourses about apps and specific features are, in our view, an important part of the development of formatting on social media, not least in some mediated form: for example, Influencers, a special tier of users, as we will see below, are instrumental in setting models of communicative practices around specific features. As metrics are an integral part of designing stories, of values in their design and of resulting formats and their recognizability, we have considered it important to tap into apps’ own views and discourses of what constitutes a story and to get a handle on the agendas behind the latest intensified ‘curation’ of stories as metricized activities, so as to assess more fully the actual offerings and affordances that accompany a story. Tracking the Design of Stories Small stories research has incorporated in its methods an element of real-­ time tracking and of critical moments both in terms of the evolution of ego-centred apps and in terms of specific events that become social-­ mediatized, thus giving a sense of the workings of social media and their affordances. A critical moment (Vaajala et al. 2013) encompasses micro-­ scale events or incidents that may serve as a disruptive moment that sets larger processes in motion: they may, for instance, provide a glimpse of meanings, ideas and values that are normally taken for granted or remain tacit, hidden and backgrounded under ‘normal’ circumstances. Such moments may allow ‘condensing a complex subject […] to a few symbolic issues’ (Oberhuber et al. 2005, 230). In that respect, the introduction of Stories as a distinct feature is arguably a critical moment in the evolution of both Snapchat and Instagram. In fact, it is a pivotal element of the third design phase that Georgakopoulou’s genealogical tracking of ego-centred apps (mainly Facebook, Instagram, Snapchat)7 combined with the analysis of users’ communicative practices has allowed her to identify, concerning facilities for the presentation of the self through stories (Georgakopoulou 2017). The first design phase goes back to the inception of social networking sites as spaces for sharing the moment now, with a premium on brevity and based on an algorithmic pressure for immediacy. Georgakopoulou has

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demonstrated how this economy of breaking news prompts users to share their everyday life as small stories, that is, as brief, fragmented, share-as-­ you-go snapshots of daily, often mundane, life (2014, 2015, 2018). The second major design phase has involved the move from sharing the moment now with text-based representations (i.e. telling the moment) to showing the moment. This was enabled and encouraged with facilities for geo-location, shared check-ins and visual affordances, in particular selfies, which rose in popularity in 2013 (Georgakopoulou 2016a, b). The third and latest design phase (covering mainly the period post-2015), sharing the moment(s) as stories, involves the rolling out of facilities explicitly branded as memory (e.g. Facebook memories) and story facilities that purport to allow the users to post beyond single feeds and beyond being confined to ‘a single moment’ (e.g. Moments on Twitter). A lens on these features needs to take into account the historicity of choices and the backlashes, which often lead to the apps updating their features in response to users’ (performative) uptake. This game of perpetual change and mutually feeding relationship between apps’ evolution and users’ practices often involves co-opting user resistances by bringing their ‘vernacular strategies’ into the apps’ ‘officialdom’ (Abidin 2018, 92; also see Bucher 2018). As we will see below, Stories are in many ways part of an evolution especially of Instagram that takes into account, co-opts and remedies previous backlashes, especially around the pristine pictures. Real-time tracking and identification of critical moments become part of a process of ethnographic tracing of the workings of technology in relation to the design of stories, part of a ‘technography’ of stories, to use Bucher’s term (2018, 60). Corpus-Assisted Methods Corpus-assisted discourse analytic methods were employed as one facet of tracking and a technographic approach to stories: media app companies’ briefs and blog posts, documents that outline technical specifications of new features and media reports are all part of a machinery of texts that afford a sense of the values in design perspective. Corpus-assisted methods allow us to analyse such texts by going beyond ‘naked eye’ observations to retrieving meanings and associations that are salient yet not obvious and that can only be established by seeking out patterns of occurrence in a body of texts. Keywords, collocations and lexical associations are an important part of such patterned meaning-making and connections,

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bringing to the fore traces of social routines and habitual patterns of understanding and acting (Taylor and Marchi 2018, 61). In the light of the above, Georgakopoulou and Drasovean (2018) employed advanced Google search facilities on the words ‘stories’, ‘Instagram’, ‘Snapchat’ and ‘Facebook’, and the search engines Google, Bing and DuckDuckGo,8 so as to compile a corpus of material (c. 1213 articles, excl. duplicates and 1,000,000 words) related to the introduction and review of Snapchat Stories (2014) and Instagram Stories (2016).9 The main types of sources in the obtained corpus (henceforth the Ego-Media Stories corpus) include Instagram/Snapchat blogs (https://instagrampress.com/blog, https://www.snap.com/). Combined with those are presentations and reviews of such features on online media: (a) Tech and digital magazines and blogs: for example, Buzzfeed, TechJunkie, The Verge, Macworld, The Next Web, TechCrunch and Wired. (b) Business/online marketing magazines and blogs: Sprout Social, Marketing Land, Forbes, Business Insider and searchenginejournal.com The publication dates include the time interval May 9, 2012–January 30, 2018. Figure 4.1 shows the distribution of the articles over time. The spikes in the graph represent key-events in the evolution of Stories (e.g. August 2, 2016—Instagram launches stories). Using corpus compilation and corpus analysis procedures (for details, see Georgakopoulou 2019),10 we identified keywords and key semantic domains,11 collocates so as to explore the textual behaviour of keywords and concordances so as to explore patterns of lexical associations.

Article frequency 60 40 20 0 09/05/2012

09/05/2013

09/05/2014

09/05/2015

09/05/2016

09/05/2017

Fig. 4.1  Distribution of online articles about the Story feature over time (May 9, 2012–January 30, 2018)

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Having analysed the corpus, we funnelled down (Marchi 2010) from identified patterns to micro-analyses of stretches of data with consideration on the basis of corpus analysis insights to further micro-­analysis of selected processes. These insights in turn led us to the next phase of collecting data from Influencers (see below). The fact that qualitative, multimodal analysis of online media posts about stories had been carried out prior to the corpus compilation and that a parallel, sampled analysis of whole articles took place mitigated the context impoverishment involved in any corpus compilation when multi-modal data are involved. Communicative Practices: A Case Study of Influencers’ Stories As suggested above, directives to specific types of behaviour and interaction should not be viewed as determining users’ practices but requesting and encouraging certain actions. On this basis, we have opted for including in our portfolio of materials a focus on actual use, that is, on users’ practices of posting stories. Power, hyper-popular users were, in our view, the first necessary point of entry into practices for two reasons: the style and content of Influencers’ communication, including their Stories, are highly emulated by ordinary users. The apps themselves tend to evolve their features based on Influencers’ practices, indeed on Influencers’ resistances (cf. Abidin 2018; Bucher 2018). We saw above how access to metrics and tracking of story analytics privileges business accounts with over 10,000 followers, thus rendering certain metrics more visible to specific users. It is also worth noting that Instagram is currently rolling out new creator profiles for Influencers, offering exclusive features and analytics. Instagram Influencers are often referred to in the tech industry as the app’s MVPs (Most Valuable Players). This particular group also complicates the difference between interface metrics visible to users (e.g. the Like score) and algorithmic metrics invisible to users. This happens as Instagram introduces what we will call ‘MVP metrics’ that make the normally invisible backstage of platform statistics visible to privileged Influencers able to reach a specific target of followers. The introduction of MVP metrics underlines that access to metrics have become a performative capital of its own, but one that in this case is only available (as a resource for improving future traction) to those already able to produce value on and for the platform (https://later.com/blog/instagram-creator-profile/).

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The first phase of a multi-phased ongoing study of Influencers’ Stories involved selecting two, in many ways representative, cases of female12 Influencers. Here, we present findings from data from Lele Pons, (https://www. instagram.com/lelepons/?hl=en), an American-Venezuelan Instagram and YouTube celebrity and former top female Viner, with the most watched Stories, according to Instagram’s released figures. The data collection has involved mining Stories (as multi-modal data with their metadata) from these two Influencers, in an automatic collection period of 20 days in January 2019 (data collected by Anda Drasovean), using Python command line tools and Instaloader. Part of the data collation and workup involved using Python tools to convert the time of posting metadata into the Influencers’ local time of posting. Our view was that it was important, as part of getting a handle on practices of posting Stories, to have a sense of routine engagements in relation to the cycle of the day, which serves as the main temporally organizational unit for posting Stories. (This is due to the fact that Stories, unless archived, disappear after 24 hours.) The data of this first phase amount to 406 Stories by Lele Pons. Our subsequent coding of stories on NVivo12 included metadata, types of captions, language of choice in captions, interactive elements (e.g. swipe up features), format of Stories (e.g. live, photos, videos), mentions in Stories of others and so on. We also coded Stories in terms of the type of experience they encoded, using certain categories13 that had emerged from a qualitative, social semiotic analysis of the Stories, for instance, good morning/good night Stories, on-the-go Stories, promotions and so on.

4.4   Analysis Directive I: Sharing-Life-in-the-Moment The first directive attested to in our analysis goes hand in hand with the apps’ logic of ephemerality and sharing the moment. Stories are built on the basis of the algorithmic logic of instant, live sharing and become a format for capturing the moment.14 This is despite the rhetoric of the apps in launching Stories as a means for allowing users to go beyond the moment (see Georgakopoulou 2019, on mismatches between the apps’ rhetoric about stories and the actual affordances offered for them). It is notable that in the Ego-Media stories corpus the lexeme ‘moment(s)’ is one of the top 50 keywords, and it mostly collocates with ‘share/sharing’

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. This suggests the close association of Stories with sharing moments, which is a far cry from the conventional definition of stories as reports of past events, evaluated and reflected upon by the narrator. The most frequent modifiers for moment (see Table 4.1), often used in the plural, can be grouped semantically in three broad categories: 1. everyday, little, casual, daily 2. special, favourite, funny, beautiful, perfect, interesting, authentic 3. fleeting, brief Moments are thus associated with spontaneity and the mundane, reinforcing the deployment of stories for sharing the everyday as it happens and as ‘multiple’, ‘little’ moments and occasionally for adding an aesthetic quality to the banal occurrences of life (Ibrahim 2015) . This contrasts with the two most frequent meanings of moment in the British National Corpus (BNC), namely moment as a very short time interval (e.g. a brief moment) and as an opportune and specific occasion (e.g. at the last/crucial/right moment). Such conventional associations for moment are absent from our corpus in favour of new associations, especially with the mundane. In a similar vein, the analysis of the collocates of the lemma story (see Table  4.2) shows that the association between stories and memories, Table 4.1  Partial word sketch for moment Modifiers of ‘moment’

Verbs with ‘moment’ as object

Verbs with ‘moment’ as subject

Collocate

Score

Collocate

Score

Collocate

Score

share twitter everyday favourite special funny brief life behind-the-scenes fleeting particular little

10.55 10.13 9.99 9.74 9.19 8.78 8.7 8.64 8.58 8.52 8.46 8.46

share capture revisit make curate highlight create save show give post see

11.33 11.17 8.5 8.45 8.3 8.3 8.08 8.02 7.94 7.57 7.51 7.2

be have

7.50 7.01

‘moment’ and/or story stories

9.13 7.70

possessors of ‘moment’ life 12.41 world 12.37 twitter 11.14

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Table 4.2  Most salient verbs that take story as an object in the Ego-Media Stories, British National Corpus, English Web 2015 and TED_en corpora Ego-Media stories

BNC

Collocate

Score

Collocate

view watch tell create see post hide save share bring make have open delete select be add tap download screenshotted

11.45 10.87 10.84 10.79 10.26 10.06 9.86 9.55 9.38 9 8.88 8.53 8.17 8.15 8.11 7.98 7.97 7.81 7.8 7.54

tell hear read write recount believe invent cut relate finish know retell publish continue begin illustrate remember print narrate move

English Web 2015

TED_en

Score

Collocate

Score

Collocate

Score

10.29 7.67 7.59 7.57 7.39 7.37 6.77 6.77 6.71 6.62 6.59 6.45 6.39 6.08 6.02 6.02 5.97 5.95 5.91 5.85

tell read share hear write recount publish retell narrate know love relate be move cover break remember feature run follow

11.34 9.11 9.03 8.19 7.79 7.06 6.97 6.95 6.83 6.62 6.46 6.3 6.29 6.28 6.21 6.19 6.05 6.03 5.97 5.94

tell hear write share cut remember know start be make become

10.62 8.15 8.12 8 7.99 7.31 6.52 6.2 6.15 5.84 5.67

which is salient in the British National Corpus (BNC), is absent from our corpus, providing further evidence for the close association of stories with the present moment and ephemerality. In addition, the analysis of the key semantic domains suggests that immediacy is a salient theme in the corpus, as can be observed in the highlighted semantic fields ‘Time: Future’ (row 14) and ‘Time: Present; simultaneous’ (row 20) of Table 4.3.15 The importance of immediacy, ephemerality and timeliness is supported, if not shaped, by metrics. Timeliness is notably one of the keyfeatures of Instagram algorithms, and it is supported by Instagram prioritizing use of mobiles and locative media able to catch and share life on the move. In fact, the types of Stories that we found in Lele Pons’ data are, what we would call, small-story formats well suited to the directive of sharing life-in-the-moment with the algorithmically favoured timeliness of postings (Fig. 4.2).

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Table 4.3  20 most salient semantic domains in the Ego-Media corpus and most frequent words assigned to them Rank Freq. in study corpus

Log-­ likelihood value (LL)

Log-­ likelihood ratio

Semantic domain Most freq. words

1

2150

2173.72

1.87

Speech: Communicative

2

701

996.04

2.34

Using

3

654

785.25

2.09

Arts and crafts

4

3403

783.41

0.79

Unmatched

5

435

649.6

2.42

6

358

511.99

2.35

The Media: TV, Radio and Cinema Information technology and computing

7 8

286 8194

506.55 406.27

2.72 0.35

9

731

402.12

1.3

stories, story, content, said, say, comments, says, told, talking, conversation, talk, point, comment, saying, spoke, note, mentioned users, use, using, user, used, uses, function photos, photo, camera, icon, pictures, picture, design, draw, drawings, drawing Instagram, snapchat, app, apps, whatsapp, slideshow, screenshot, Canva, Stacy, emoji, geofilter, iphone, Ingrid, username, millennials, Shopify, emojis, storytelling video, videos, viewers

screen, upload, blog, website, web, digital, online, messaging, downloaded, computer, https Reciprocal share, sharing, shared, shares Pronouns you, your, it, that, i, they, their, what, she, we, them, who, this, her, which, my, its, something, he, our, us, me, someone, his, one, everyone, everything, those, itself, these, anyone, anything, their_own, your_own, him, ones, whatever, yourself Paper documents post, posts, text, page, archive, and writing posting, posted, list, delete, stickers, record, recording, edit, tag, deleted (continued)

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Table 4.3 (continued) Rank Freq. in study corpus

Log-­ likelihood value (LL)

Log-­ likelihood ratio

Semantic domain Most freq. words

10

503

279.17

1.3

11 12 13

183 31 292

177.73 147.6 141.42

1.83 7.62 1.2

14 15

542 349

135.72 130.08

0.83 1.04

General appearance and physical properties The Media Business Business: Generally Time: Future Business: Selling

16 17

326 619

123.31 115.73

1.04 0.71

If Wanted

18

443

113.1

0.84

Sensory: Sight

19

1171

102.93

0.47

Likely

20

428

100.83

0.8

Time: Present; simultaneous

feature, image, twitter, images, features, format, ready

media, publish, published rolling_out business, company, businesses, b2b, companies will, ’ll, going_to, soon, future marketing, ads, customers, marketers, sales, buy, store, advertisement, advertising if want, choose, strategy, option, select, options, wanted, choice see, watch, seen, watching, look_at, seeing, visual, watched, visible can, would, could, may, might, can, probably, likely, sure, make_sure, possible, clear, potential now, update, daily, yet, today, current, currently, updates, right_now

These include: Friends and family: Stories that show or mention the poster’s friends or family typically in fun outings or domestic life scenes (e.g. hanging out, eating, watching TV). Good morning/good night Stories: Pictures and videos that contain greetings such as ‘Good night’ or ‘Good morning’. On the go: Pictures/videos from the poster’s trips abroad, day trips, road trips with friends and so on.

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Fig. 4.2  NVivo coding of Lele Pons’ stories

Promotions: This category can be broken down into: Self-promotion: Pictures/videos that show the Influencer in her professional capacity (e.g. dancer, singer, model), mention her accomplishments or announce the publication of new content on Instagram or YouTube. Endorsements: Promotions that mention (with hashtag) collaborators (singers, dancers, make-up artists). Product tutorials: Videos showing how to use a product (e.g. apply make-up). The above formats have in common that they single out for sharing snapshots from the here-and-now of daily life. In tune with Instagram’s template Stories, Lele Pons’ Stories routinely show moments from her everyday life, for instance fun outings with friends (e.g. girls’ night out) and her travelling, and they tend to be accompanied by heart emojis and brief captions that serve as a description and assessment of what is going

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on (e.g. Milan next to a sign of a plane in a picture of Lele Pons at an airport). With a premium on timeliness, Stories become an integral part of the users’ attention economy, fuelled by (audio)visual moments of affective intensity and satisfying distraction (Paasonen 2016). It is, indeed, clear that metrics in stories have been designed so as not just to capture attention but also to retain it, maximizing the followers’ time spent on engaging with them. The shift to a streaming culture (Abidin 2018) typified by Stories is also aimed at keeping both posters and followers active and coming back. This inevitably leads to frequency of postings, as we can see in the Influencers’ data, despite the fact that Stories were explicitly introduced as a means of remedying over-posting.16 Market research on Instagram Stories posted by businesses has found that one to seven Stories is the optimal posting length (https://buffer.com/resources/instagramstories-research). Lele Pons falls on the top end of this posting frequency, making the most of her enormous fan base and integrating Stories into the sharing-live-and-sharing-now economy linked with pressures to keep their followers’ attention. Lele Pons for instance adds content (mostly pictures and videos and fewer live Stories) several times a day (every 2–3 hours). Her Instagram Stories for one day are thus a veritable newsfeed designed to keep her followers engaged 24/7. One of the strategies she employs as a resource for multiple postings and for keeping followers’ attention is to produce countdown sequences: a breaking news format announces an upcoming event or happening with a temporal indication followed by countdown updates, again with temporal markers. It is very common to present such stories as a countdown sequence: for instance, Lele Pons posted a sequence of three Stories within one hour in the lead up to the release of her video Amigos (a short video parody of the TV show Friends’ opening credits, featuring Lele Pons and five other friends and replacing the well-known Friends theme with a Latino song). The first story was announcing that the video would be ‘coming out in 1 hour’, the second that it would be out in 30 minutes and the third that it was ‘out now’. Directive II: Audience Engagement as Quantified Viewing  etrics and Tiers of Invisibility M As suggested, the directives in the design of metricized stories are supported by evolving affordances that seem to be making the project of

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metricizing every single aspect of a story possible. The evolution of metrics, specifically, has been done in ways that allow cross-syndication and increased data flow, for instance, by allowing posters to link their Stories with other content, to use hashtags and location stickers. A case in point is the Paperclip icon on Snapchat which lets everyone,17 from ordinary users to advertisers, attach an external web link to their Snaps for their Stories. Stories with such content-linking features can be included in the Search and Explore page of Instagram: this is done in the name of a story’s ‘discoverability’ by other users, but ultimately, as we will see below, all such features add layers of metricization to a story. For instance, if a story gets featured in a hashtag or location story by Instagram, the number of viewers who viewed it through the Instagram Explore page can be tracked. Evolving affordances also include facilities for audience engagement (e.g. by replying to a story with comments that go to the poster’s inbox and, as things stand, remain private) as well as for audience selection: posters, for example, can mention and tag up to ten people. These affordances too are part of the project of metricizing every single aspect of a story. Currently, key-metrics both on Snapchat and on Instagram include not just the total number of a story’s views but also the total number of story completions: for example, the number of users who may have opened up the first frame of a Snapchat Story but then abandoned it and similarly on Instagram those who skipped a story (to go to the next account’s story) or exited it (left the story to return to their feed). Measurements of engagement become fine-tuned, in terms of level and depth of engagement. For instance, completion rate is the percentage of people that started viewing a story compared to how many of them saw the last part of a story. Numbers of screenshots of Snapchat Stories show how many times a story has been viewed. On Instagram, an important engagement-gauging tool is the distinction between impressions (the total number of views a story has received) and reach (the number of unique accounts who saw a story). Overall, one can talk about a saturation of numbers at every level of the storytelling process, including features (e.g. location stickers) that are rolled out on the face of it to enhance the actual content of a story. As these become measurable (cf. tap-able) too, we get into a situation in which engagement with Stories not just in their entirety but also as segmentable parts (e.g. slides, links, stickers) is countable, quantifiable and tractable. Metrics in turn come with multiple, complex layers of stratified visibility separating users and posters from audiences in terms of access to metrics and duration of tracking facilities: for instance, you can see your own story

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analytics using Instagram tools (e.g. Insights,18 see https://help.instagram.com/1533933820244654) if you have a business account and over 10,000 followers. Such tools are constantly evolving to allow longer and more detailed tracking facilities to ‘special users’, who are given access to personalized ‘vanity metrics’, making it possible to both document and improve the social circulation of their stories (Rogers 2018; Gerlitz and Lury 2014). Business accounts also allow access and use of certain features (e.g. adding links to a story),19 which are also measurable. As an ordinary user, you can view how many people have viewed your story but your followers cannot, unless it is a live story, a recent feature. You can have longer tracking facilities if you have a business account. Instagram thus seems to be offering a helping hand to ‘valued’ users in terms of their visibility of metrics. Overall, the design of metrics seems to support the hybrid roles of stories as creations and consumable products, and it undermines the, on face of it, and in the app’s rhetoric, flat ontology of users, that is ordinary users, Influencers and businesses, as a level-playing field. The apps’ promise of user control and creativity was notably found to clash with the abundance of pre-selections, prior categorizations of experience, templates and menus with specific editing features (Georgakopoulou 2019). In turn, Stories function as a site for intensifying curation by pulling together (cf. bundling) complex resources and tools. This is in tune with the gradual evolution of Instagram from a photo-sharing app to a social network app with social interaction at its centre (Poulsen 2018): Stories have been an important step in this evolution. It is notable in this respect that Instagram is rolling out constantly new features for Stories and related metrics that allow tracking of every single action that viewers of stories take. By the time this goes to print, we can safely assume that more metrics will be in place. As things stand, some of the newest metrics include Directions, Calls, Texts, Emails: these track and measure the effect that Instagram Stories have on the action performed on a user’s profile call to action (CTA) buttons. These are essentially traffic-­ driving measures which attest to the ever-closer links of Stories with businesses: over 50% of businesses on Instagram worldwide have tellingly created at least one Story during a typical month; one-third of the most viewed Instagram Stories are from businesses, and one in five Stories from businesses generate a direct message from a follower, potential client or customer.20

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Alongside this unprecedented proliferation of metrics for one single feature of the platform, there is constant development of software by Instagram as well as third-party tools that allow better, more fine-tuned and longer access to story analytics as well as ways of handling them as large-scale ‘data’ (e.g. EmbedStories, Later; https://embedsocial.com/ blog/instagram-stories-analytics/). This is a clear example of metricization serving as a powerful tool for the datafication of users’ activities and for the apps’ agenda of ever-closer links with advertising. Quantified Viewing The evolution of metrics in Stories, as discussed above, clearly supports and prompts specific types of audience engagement. The viewing experience and its concomitant quantification are key to this engagement. Unsurprisingly then, the lemmas ‘story’ and ‘stories’ strongly collocate with a visual language (e.g. watch, view, see, hide, appear, disappear; see Table 4.4). Table 4.4  Verb collocates of ‘story’ Ego-Media stories

BNC

Collocate

Score

Collocate

view watch tell create see post hide save share bring make have open delete select be add tap download screenshotted

11.45 10.87 10.84 10.79 10.26 10.06 9.86 9.55 9.38 9 8.88 8.53 8.17 8.15 8.11 7.98 7.97 7.81 7.8 7.54

tell hear read write recount believe invent cut relate finish know retell publish continue begin illustrate remember print narrate move

English Web 2015

TED_en

Score

Collocate

Score

Collocate

Score

10.29 7.67 7.59 7.57 7.39 7.37 6.77 6.77 6.71 6.62 6.59 6.45 6.39 6.08 6.02 6.02 5.97 5.95 5.91 5.85

tell read share hear write recount publish retell narrate know love relate be move cover break remember feature run follow

11.34 9.11 9.03 8.19 7.79 7.06 6.97 6.95 6.83 6.62 6.46 6.3 6.29 6.28 6.21 6.19 6.05 6.03 5.97 5.94

tell hear write share cut remember know start be make become

10.62 8.15 8.12 8 7.99 7.31 6.52 6.2 6.15 5.84 5.67

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The analysis of collocates of the keywords view and watch also demonstrates the close links of modes of engagement with stories and metricization. Both keywords frequently co-occur with wh-words and quantifiers (e.g. many, number, times) to form recurring multi-word sequences (e.g. see who has viewed your story, see how many people have viewed your story) (Fig. 4.3). Engagement with a story and enjoyment out of it is thus proposed and designed as a measurable, status-accruing activity. Similarly, the word ‘audience’ and other affiliated terms (e.g. followers, users, engagement) are frequently associated with metricization lexis, such as the following: –– –– –– –– ––

nouns: count, growth, metric, numbers, rate; quantifiers: more, high, as much as; numerals: x million, x [times]; frequency adverbs: regularly, frequently, consistently; and verbs: gain, engage, grow, build.

These associations suggest that quantification is a recurring trend in the context of engagement with a story that is, in turn, closely linked with measuring and growing a story’s audience size and level of engagement. To probe more into this connection between how audience engagement in a story is envisaged, designed for and encouraged and metricization, we explored metricization lexis with the help of automated thesauri (automatically generated list of synonyms and/or semantically related terms). The Thesaurus function works by grouping a word’s collocates based on 1

well, anyone can choose to to follow you. To see who has been

viewing

the snaps on your story, go to the Stories screen as

2

rates. Yes, you are able to take a look at how many people

viewed

your story on Instagram, however, you can't see how

views

if the first two or three minutes after I post a story. Today

3

away views from stories. Generally, I receive about 100

4

how many times an Instagram video or image in their feed was

5

, this is probably a great way to up its numbers and get more

6

you to see how many times your video was viewed and who watched it. Marketers can get a better idea of their interacting by

7

before they disappear completely. Also, whenever you

viewed views

watch

more generally, according to the number of "likes" it to more stories, but the costs (to people's time?) might be

a friend's story it notifies them that you've seen it.. Well

8

story has been seen. This is a good way to see if people are watching your story multiple times , which may mean that they are

9

there (read: 1762) is the total number of people who have watched your stories so far. While you're watching InstaSnap (I

10

Instagram feed, if you fancy. Can I see how many people have watched it? Again, yes. When watching your own story, at the

Fig. 4.3  Example concordance lines for view and watch + quantifying expressions (e.g. ‘how many’)

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their grammatical function (i.e. generating a word sketch) and then comparing these collocates with the collocates of all the words in the corpus that belong to the same part of speech. What this means is that Thesaurus groups together words that are found in similar contexts. The Thesaurus for the top 20 synonyms for key metricization lexis, such as ‘rate’, clearly shows a strong association between metrics and engagement (Fig. 4.4): Bringing together these two essentially different semantic domains is also attestable in the Thesaurus for the word ‘engagement’ (Fig. 4.5). There is an evident association with quantification, on the one hand, and with quality of relationship, experience and interaction, on the other hand. This chain of associations is extended to story creativity. Georgakopoulou (2019) has shown how creativity and the teller’s control of ‘telling’ their story are abundant in the rhetoric of Instagram and Snapchat. In this rhetoric, creativity does not seem to be associated with metrics. As in other cases, the association is hidden and mediated. For instance, there is a strong association in our corpus between creativity and tools (as in using tools creatively), on one hand, and metrics and tools, on the other hand. We could thus argue that creativity and engagement are indirectly associated through their mutual association with tools. This indirect association could be interpreted as further narrowing the users’ alleged creative freedom: not only is creativity confined to using a limited set of tools but the availability of complex analytics also favours some tools Fig. 4.4  Semantic field of ‘rate’

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Fig. 4.5  Semantic field of ‘engagement’

over others, based on their efficiency in generating views and engagement: for example, ‘hashtags increase chance of engagement by over 12 percent’ (http://marketingonly.strikingly.com/blog/what-is-an-instagramvideo-view). The above results clearly show that the relational, social and creative aspects of stories as a multivalent feature (Marres 2017) are proposed as being intertwined with the quantifiable. Following Lupton’s (2016, 97) adaptation of the notion of commensuration (Espeland and Stevens 1998), we can describe this relationship between metricization and audience engagement, as envisaged in the design of Stories, as one of commensuration: the two themes in our corpus represent fundamentally different qualities which come together in ways that both confer some kind of homogeneity on their diverse meanings and begin to produce new forms of understanding them. In this case, the analytics involved in viewing a story become commensurate with audience engagement and involvement in it. This type of app infrastructure in which social interactivity and affectivity through posts are measurable and can thus be turned into valuable consumer data has been argued to be intensified by Facebook through multiple actions that are afforded by convergence and cross-syndication of apps. Users’ navigation between related apps ultimately feeds data back into Facebook (Gerlitz and Helmond 2013). Updates that are aimed at further sedimenting the collapse of the social with the quantifiable and traceable are evidence of an ongoing and potentially scalable process

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(idem). The ways in which friendship and followership are computed on Facebook and Instagram are clear antecedents of the quantification of social relations we note in Stories too, directing users to re-imagine them (Gillespie 2016). The commensuration of engagement and metricization in stories is also in tune with Abidin’s (2018, 95) claim that Influencers are increasingly conflating attention with affection economy. Directive III: Authenticity in Tellers’ Self-Presentation Our corpus analysis of how Stories were introduced and launched as a distinct feature showed that the apps’ product management of them was especially preoccupied with offering users’ tools for constructing authenticity in the sense of presenting ‘real’ (non-polished, non-filtered) selves. Media scholar Gunn Enli has argued that authenticity becomes a crucial currency on social media, where the ‘organisational trust’ in traditional broadcast media is replaced by a ‘personal trust’ in particular individuals that are powerful and worth following only to the extent that we feel them, understand them as sincere and find them authentic (Enli 2015). It is also indicative of this that creativity, authenticity and originality were strongly associated in the corpus. For instance, keywords and phrases such as create, creative, much creativity, creating content, own story and exclusive content indicate emphasis on using the Stories feature creatively, and on being an authentic, original, ‘popular’, ‘cool’ and ‘great’ storyteller (Fig. 4.6).

Fig. 4.6  Semantic field of ‘creative’ (as word cloud)

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Authenticity was specifically associated with the notion of ‘imperfect sharing’, presented as a feature of the story design that had taken on board the backlash from posting ‘glossy, perfect lives’ (Constine 2016) and the moral panic about posting edited selfies as a narcissistic activity (Georgakopoulou 2016a).21 Story design also appeared to have co-opted a discourse circulating for a while about the need for online self-­ presentation to be authentic and ‘real’ (Marwick 2013). Kevin Systrom, Instagram CEO at the time, suggested that ‘Stories creates a place for content that’s not “good enough” for the Instagram feed, or at least is too silly to fit in amongst the art.22 Because everything disappears, you don’t have to be ashamed of that awkward face or stupid joke forever the way things posted to your real Instagram profile reflect on you forever’. https://techcrunch.com/2016/08/02/instagram-stories/ In that way, Instagram incorporates Snapchat’s successful introduction of a tool for ephemeral sharing of silly and playful aspects of everyday life into its own platform design. It is clear from these statements and from the tools and affordances that Stories came with that they were introduced as a way of sorting out over-­ posting and perfect sharing, both closely linked in the public imaginary with the image of a self- and attention-obsessed user. Template stories offered by Instagram and how-to guides encouraged sharing everyday moments of having fun with friends. Similarly, many of the tools accompanying Stories (e.g. animal filters, the boomerang looping effect, Superzoom, a ‘party hard visual effect’) are meant at helping the posters to add funny elements to their stories. In the light of the above, story authenticity, an elusive, polysemous term in different contexts,23 has been developing associations on Snapchat and Instagram with being a creative storyteller who presents non-edited versions of ‘yourself’ and ‘your’ everyday moments. In our corpus, this is stressed through the collocations of authenticity with spontaneity and the users (ordinary users and businesses alike) affording their followers a behind-the-scenes24 feel of their everyday life (Table 4.5 and Fig. 4.7). In Jarvis’ terms (2017), this type of authenticity is about ‘sharing the underbelly’, showing ‘that you walk the talk. You ARE you’, providing evidence of lived experience: ‘It means that you’re telling this story because you BELIEVE IT—or better yet, because you’ve LIVED IT’. In Lele Pons’ Stories, sharing life-in-the-moment goes hand in hand with the type of promoted authenticity presented above. Stories of the moment, often about mundane events, capture ‘little moments’, taking us

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Table 4.5  Top 10 collocates for ‘authentic’ (ranked by logDice score) Rank

Collocate

Freq.

logDice score

1 2 3 4 5 6 7 8 9 10

being spontaneous raw tell feel rather nature storytelling brand visual

3 3 3 8 7 4 3 3 12 3

9.299 9.254 9.133 9.011 8.784 8.687 8.654 8.613 8.362 8.346

1 2

to build a relationship with their customers through authentic and personal content. Indeed, Brian Robbins of Footage The key is to make your fans feel like insiders. Authentic , behind-the-scenes content does just that. This is the

3

to post content that is real-time, spontaneous and more authentic . For brands there are a number ways Instagram Stories can be

4

and viewing Stories, you were sharing and viewing more authentic moments in someone's life. It's messier. It's maybe

5 6 7

for a company is to tell original stories that reflect authentic moments, instead of the traditional publicity that can be contests and campaigns, and drive more engagement. Authentic and visual brand storytelling is the future of marketing, pictures of food and drink, an actual story that conveys an authentic narrative has a strong chance of standing out. Adding

8 on popular user behavior, 2. It's a great way to share more authentic moments with followers, and 3. This means one less social 9

stories," says "Today's marketers need todeeper more authentic stories," says Craig Elimeliah , Director of Creative

10 re asking that because everything in my mind is about real, authentic engagement. So you need to ask some questions and you need

Fig. 4.7  Example concordance lines for ‘authentic’

behind the scenes, constructing a sense of real life and inviting the viewers to be witnesses of that reality. The narrator becomes a recorder on the spot, a narrator-experiencer as opposed to a narrator that can step back and reflect on the goings-on. Life-writing becomes life-casting, a transient, streaming format of showing the self in the here-and-now. An integral part of such storying is the amateur aesthetic (cf. Abidin 2018) which is encouraged by Instagram’s tools and template stories, comprising minimal, simple static graphics. According to Abidin, this amateur aesthetic ‘feels less staged and more authentic’ as ‘the live, moving image affordances of streaming apps tend to enable for little modification and the basic editing affordances restrict modification to preset filters and stickers’ (91). Authenticity is thus intertwined with ordinariness and the construction of a sense of a level playing field for all users, ordinary, Influencers and

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businesses, despite the fact that metrics, as we have seen, actually separate and stratify them. The currency and uptake of this amateur aesthetic is of note. The Guardian for instance found, for their Instagram Stories, that simple static graphics and quick explainer videos outperformed their professionally produced videos (https://digiday.com/media/ guardian-finds-less-polished-video-works-better-instagram/). From the perspective of the Stories’ metricization, the equation of authenticity with minimal editing and polishing time is actually a means of maximizing follower engagement with minimal time investment. The following excerpts from how-to guides about stories in our corpus are illustrative of this agenda: The stories you create that are candid and silly can often drive higher engagement than the posts you spend significant time on with editing and production. https://zenmedia.com/4-pro-tips-using-instagram-stories-marketbusiness/ The organic and off-the-cuff nature of these short videos gives users a new way to spend more time directly viewing your brand, and allows your followers to pull back the curtain and get a more nuanced view of who you are and what you do. https://mediadesknm.com/3-things-non-profits-should-considerabout-instagram-stories/

Our analysis showed that the trade-off between the time invested in creating content and the level of engagement (time spent by users to view/share that content) is expressed in the corpus by collocations such as amount of time and spend time, as in the examples above (in bold). Authenticity is thus presented as a means of maximizing return. The promise of user control and creativity was found to clash with the abundance of pre-selections, prior categorizations of experience, templates and menus with specific editing features. The directive of constructing authenticity arguably places Influencers in a double bind of navigating the competing demands of sharing ordinary life-in-the-moment with promoting themselves and their products. Our analysis shows that these competing demands are reconciled by blurring the lines between the self in ordinary life and the self as promoter (at least one-third of the stories in our corpus are essentially advertisements). This

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concurs with the widely attested function of social media as arenas for affective labour (Hardt 1999), where the self works and produces value by engaging in affective connections/exchanges and putting itself on display (McCosker 2013). Deploying small stories well suited to the directive of sharing-life-in-the-moment is the main life-casting modality for essentially conflating the Influencers’ affective, relational sharing with their followers with promoting their products. As we have seen, countdowns and behind the scenes are major vehicles for creating this conflation. Tools that Instagram offers, on the face of it, to enhance the relationality of stories, can also be mobilized for (self-)promotion. Location stickers, for instance, can advertise places (e.g. restaurants, shops, etc.). Mention stickers can advertise ‘friends’ and their ‘products’. Hashtag stickers can proliferate the likelihood of certain types of stories and in turn promotional content becoming more popular than others. Self-branding, a major attested mode of self-presentation on social media, in the service of popularity and (micro-)celebritization (e.g. see Marwick 2013; Senft 2013) gets a twist with stories: it not so much ‘yourself’ as ‘your life’ and ‘your story’ that becomes a monetizable brand. The inherent contradiction of celebritization between authenticity and visual/visible display of the self for scrutiny (Marwick 2013) has not gone away in Stories, despite them being introduced as a technology of the self that remedies the hypervisibility of selfies and the perils of perfect sharing. Stories in fact consolidate the visuality and viewability of selves, adding, as shown above, sophisticated metrics of audience engagement that are tied to the experience of stories as (re)viewable products. What changes in the case of Stories is that the relational and affective power of stories that the rhetoric about stories invokes and their design, including metrics, allow for the project of constructing authenticity to exploit the conflation between attention and affection economy.  n Algorithmically Mediated Authenticity A An authentic self is intimately linked with the sharing of an everyday, ordinary life that creates connections with the followers. The followers’ engagement with Stories appearing full-screen on their smartphones is a big part of this immersive, intimate experience. Their viewing engagements place friends and Influencers on the same level, as stories appear next to one another and can be viewed one after another. A story of your close friend going out clubbing can be next to a story from an Influencer, also clubbing, next to a story promoting a product. This visual and

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experienced contiguity and coexistence is conducive to conflating the ordinary with the promotional and, as have seen, relationality and affectivity with quantification. Authenticity therefore becomes interwoven with an algorithmically mediated and configured relationship25 between Influencer and followers, which prompts the type of affection and connection on the part of followers that Georgakopoulou (2016a, b) has called in her work on comments on selfies ‘ritual appreciation’. Ritual appreciation involves comments of positive assessments of the poster (be it of a selfie or of a story), expressed in highly conventionalized language (e.g. ‘love you’, ‘you are amazing’, ‘so sexy’, etc.) coupled with emojis (mainly hearts). These semiotic choices result in congruent sequences of atomized contributions by commenters, which despite not directly engaging with one another are strikingly similar, visually and linguistically. It is notable that the replies to stories by followers (replies are currently private) chosen to be posted as Stories by Lele Pons are akin to such ritual appreciation comments. Lele Pons often singles out such highly positive comments and posts them as Stories. Such posts are of course self-selected, and we can speculate about the number of hate messages that Influencers also receive alongside the ‘love you’ ones. The point, however, remains that interactions between followers and followed, on the basis of Stories, are in line with the type of affection economy already developed on the basis of other technologies of the self, especially selfies. For all their emphasis on ‘authenticity’, stories are presenting a strong genealogical continuity with a (micro-)celebritized display of a visual and viewable self (and life) that prompts a character-based affiliation as engagement with a story.

4.5   Conclusion This chapter has focused on stories as a designed feature on Instagram and Snapchat and the role of metrics in this design. Based on a corpus-assisted analysis of online media about Instagram and Snapchat Stories and of Instagram Stories by an Influencer as well as on a real-time technography of the evolution of Stories as a feature, we showed how the links of stories with metrics create preferential conditions (directives) for three practices for the prosumption (production and active consumption) of stories: life-­ sharing-­in-the-moment; audience engagement as quantified viewing; and the tellers’ construction of authentic selves. As we showed, these directives prompt the telling of specific tales, specific types of audience engagement and specific modes of self-presentation. These, in turn, are in a

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relationship of entanglement with different kinds of interface, content and algorithmic metrics. The directive of sharing-life-in-the-moment leads to small stories well suited to the algorithmically favoured timeliness of postings. Metrics of viewing and of completion figures of stories are entangled with audience engagement in ways that collapse affection with the audience’s attention economy. Stories connect and they are a prime relational communication format, but they also grab attention. They increase users’ dwell time in an app both as storytellers (we have seen how sharing life in the moment leads to frequent postings) and as audience (viewing a story requires 10–15 seconds of, however divided, attention). Finally, the directive of constructing authentic selves becomes an integral part of an ecology of frequent posting, as it minimizes the editing and polishing time. It also works well with the algorithmically mediated creation and reaffirmation of a relationship between storytellers and audiences that is based on frequency of ‘interactions’ (e.g. viewings). Ritual appreciation, a common conventionalized type of interaction, is more readily integrated into a time-pressed attention economy than other complex types of contribution requiring depth of engagement, for instance, collaboration in a story’s telling. These entanglements ultimately interconnect and conflate (cf. commensurate) creative, relational and affective processes of storytelling with quantification as a complex process of a continuum of more or less visible, tractable and accessible metrics. The normative potential of this commensuration for what types of stories and in turn ways of presenting the self are becoming widely available whilst silencing others should not be underestimated,26 and it should prompt further scrutiny. Similarly, there is scope for interrogating further the close links of stories with advertising on the basis of the different tiers of (in)visibility of metrics, depending on the status of users, as well as the implications of privileging businesses and Influencers as major stakeholders in the production of stories. In terms of our typology of metrics, our findings point to a tendency to fine-tune and expand on metricization affordances beyond the interface in ways in which they make engagement with discreet aspects of the content of the posting (in this case, a story) measurable. In the light of this chapter’s findings, studies of the designing of stories as quantified activities on social media require combined attention to the communicative how, the what and the who with the socio-technicity of stories and ethnographic methods that allow us to track the evolution of such socio-technicity. This includes a critical interrogation of the values

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that underlie the design of stories, the tools that accompany stories and become instruments for their valuation, and the (in)visibilities of tellers-­ tales-­audiences that these create. It is within this nexus that agency and any empowering potentials of stories for storytellers and audiences need to be placed and examined.

Notes 1. Ego networks are akin to ‘common-bond communities’ which owe their existence primarily to the fact that the members are interested in one another, as opposed to building on shared interests (Schwämmlein and Wodzicki 2012, 388). That said, as platforms are evolving, the boundaries between these traditional distinctions are eroding. 2. All references to the apps’ feature of ‘stories’ will be with capital S henceforth. 3. This applies at the time of writing the book. 4. Pre-texting also includes ‘conditions on sayability’, that is, practices, competencies and contextual frames that make it possible for certain people to credibly engage in certain kinds of interactions (Maryns and Blommaert 2002, 11). 5. Tagg and Seargeant (2016) and Georgakopoulou (2016a) have shown how users may actively do audience selection with the ways in which they design their Facebook posts so as to include their close friends more than others. 6. The material specifically comes from Georgakopoulou’s project ‘Life-­ Writing of the Moment: The sharing and updating self on social media’, part of a European Research Council-funded grant (www.ego-media.org) 7. Ego networks are akin to ‘common-bond communities’ which owe their existence primarily to the fact that the members are interested in one another, as opposed to building on shared interests (Schwämmlein and Wodzicki 2012, 388). 8. We used more than one search engine to try and minimize the biases of Google search histories in the collection of data. 9. The corpus was compiled in February 2018, and it includes material published by January 2018. 10. In brief, although we ‘cleaned up’ the texts for the purposes of the corpus analysis, it was important for us to download and have access to any visual material for any subsequent multi-modal analysis. We used the software SketchEngine for the analysis and three reference corpora: the British National Corpus, EnTenTen15 (or English Web 2015) and the TED_en Corpus (transcriptions of TED talks).

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11. We used Wmatrix to this effect, an online tool (http://ucrel.lancs/ac.uk/ wmatrix) that automates the semantic categorization process and allows the exploration of semantic fields and collocations. 12. Although the female bias in the gender ratio of Instagram users has recently narrowed, six of the top ten most followed accounts on Instagram are currently owned by women, so it is no accident that our study has begun with two female Influencers. Kim Kardashian, who has been included in the first phase of the ongoing data collection, is routinely on the top ten list. 13. We kept an open mind about a category that we called miscellaneous that could not fit into any of the above four categories. We are in the process of fine-tuning and identifying sub-categories, as we will be collecting more Stories. One sub-category that we have clearly identified in Lele Pons’ case is ‘humour’ that comprises funny, goofy Stories, in the tradition of the slapstick genre of the vines that made her famous in the first instance. 14. Instagram, like Facebook, discloses specific key-features of its algorithms, inviting users to a guessing game about its largely opaque calculations. Three such key-features involve timeliness, relationship and interest. As we will see, these are important considerations in how both interface and content metrics are designed by Instagram as well as in how they are put to practice by Influencers. 15. The table presents the 20 most salient semantic domains (ranked by log-­ likelihood value and relative to BNC, our reference corpus) and the most frequent words assigned to these domains (with a freq. > 10). 16. This was Instagram’s rhetoric about Stories, but Abidin’s point that Instagram’s evolution has been aimed at curtailing cross-platforming so that its users ‘content dump on its platform and […] post more frequently by breaking the previously established practices of users posting only at optimal times’ (2018: 89) is readily applicable to Stories. 17. It is fair to assume, however, that connecting their presence on Snapchat to other locations on the web is mostly done for the benefit of corporate brands and so as to encourage ordinary users to go to the websites of such brands to check out products. 18. Button in the top right corner of your Instagram business profile. 19. The first time that users are allowed to add links to Instagram content that are not the link in their bio. 20. h t t p s : / / s u p p o r t . s o c i a l r e p o r t . c o m / h c / e n - u s / ar ticles/115005343286-Instagram-Stories-Vs-Snapchat-Stories2017-Statistics 21. My ethnographic tracking of a group of female teenagers whose selfies I analysed (2016a) suggested their move to Snapchat and then Instagram Stories as a more ‘authentic’ way of presenting themselves and their lives than selfies.

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22. This is arguably another ‘influence’ from the way in which Snapchat, and Stories within it, was designed as a tool for imperfect sharing amongst youngsters (see Kofoed and Larsen 2016). 23. Authenticity, especially in terms of the narrator’s honesty, reliability and trustworthiness as well as in terms of the reported events’ and experiences’ accuracy, verifiability and credibility has always been an issue with personal experience stories. It has also been at the heart of narrative studies’ concerns. 24. Behind the scenes is a recurrent phrase in the corpus (it occurs 179 times in total), which is indicative of the promoted spontaneity and authenticity. 25. It is notable that the friends and family category is recognizable and programmable to algorithms as those people who interact most with you. 26. Georgakopoulou (2019) argues that the creation of normative patterns of storytelling is expected to be more attestable in the apps’ initial target groups of stories amongst ordinary users, namely teenagers and young adults.

References Abidin, Crystal. 2018. Internet Celebrity Understanding Fame Online. Bingley: Emerald Group Publishing. Bamberg, Michael, and Alexandra Georgakopoulou. 2008. Small Stories as a New Perspective in Narrative and Identity Analysis. Text & Talk 28 (3): 377–396. Beer, D. 2009. Power Through the Algorithm? Participatory Web Cultures and the Technological Unconscious. New Media & Society 11: 985–1002. Blommaert, Jan. With Szabla, M., Maly, I., Procházka, O., Lu Ying, and Kumming, L. 2019. Online with Garfinkel. Essays on Social Action in the Online-Offline Nexus. Tilburg Papers in Culture Studies, Paper 229. Tilburg University. https://www.tilburguniversity.edu/research/institutes-and-research-groups/ babylon/tpcs. Bucher, Taina. 2012. Want to be on the Top? Algorithmic Power and the Threat of Invisibility on Facebook. New Media & Society 14 (7): 1164–1180. https:// doi.org/10.1177/1461444812440159. ———. 2018. If … then. Algorithmic Power and Politics. Oxford: Oxford University Press. Carlson, Matt, and Seth C.  Lewis. 2018. News and the Networked Self: Performativity, Platforms, and Journalistic Epistemologies. In A Networked Self and Platforms, Stories, Connections, ed. Zizi Papacharissi, 29–42. London: Routledge. Constine, J. 2016. Instagram Launches ‘Stories’, a Snapchatty Feature for Imperfect Sharing. Accessed 10/11/2019. https://techcrunch.com/2016/08/02. Cooper, S. 2016. Snapchat Versus Instagram: The War of the Stories. Accessed 10/11/2019. www.thedrum.com/opinion/2016/08/25.

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Marwick, A. 2013. Status Update: Celebrity, Publicity, and Branding in the Social Media Age. New Haven, CT: Yale University Press. Maryns, Katrijn, and Jan Blommaert. 2002. Pretextuality and Pretextual Gaps. Pragmatics. Quarterly Publication of the International Pragmatics Association (IPrA) 12 (1): 11–30. McCosker, Anthony. 2013. Intensive Media: Aversive Affects and Visual Culture. Basingstoke: Palgrave. Oberhuber, Florian, Christoph Bärenreuter, Michał Krzyěanowski, Heinz Schönbauer, and Ruth Wodak. 2005. Debating the European Constitution: On Representations of Europe/the EU in the Press. Journal of Language and Politics 4 (2): 227–271. Paasonen, Susanna. 2016. Fickle Focus: Distraction, Affect and the Production of Value in Social Media. First Monday 21 (10): 1–14. Poulsen, S.V. 2018. Becoming a Semiotic Technology  – A Historical Study of Instagram’s Tools for Making and Sharing Photos and Videos. Internet Histories 2 (1–2): 121–139. https://doi.org/10.1080/2470147 5.2018.1459350. Rogers, Richard. 2018. Otherwise Engaged: Social Media from Vanity Metrics to Critical Analytics. International Journal of Communication 12: 450–472. Schwämmlein, E., and K.  Wodzicki. 2012. What to Tell About Me? Self-­ Presentation in Online Communities. Journal of Computer-Mediated Communication 17: 387–407. Senft, Theresa M. 2013. Microcelebrity and the Branded Self. In A Companion to New Media Dynamics., ed. J.  Hartley, J.  Burgess, and A.  Bruns, 346–354. Oxford: Blackwell. Tagg, Caroline, and Philip Seargeant. 2016. Facebook and the Discursive Construction of the Social Network. In The Routledge Handbook of Language and Digital Communication, ed. A. Georgakopoulou and T. Spilioti, 339–353. Abingdon: Routledge. Taylor, Charlotte, and Anna Marchi, eds. 2018. Corpus Approaches to Discourse: A Critical Review. Abingdon: Routledge. Vaajala, Tiia, Ilkka Arminen, and Antoon De Rycker. 2013. Misalignments in Finnish Emergency Call Openings: Legitimacy, Assymetries and Multi-tasking as Interactional Contests. In Discourse and Crisis: Critical Perspectives. Amsterdam and Philadelphia: John Benjamins. Van Dijck, Jose. 2013. The Culture of Connectivity. New  York: Oxford University Press. Van Dijck, José, and Thomas Poell. 2013. Understanding Social Media Logic. Media and Communication 1: 2–14. Van Dijck, José, Thomas Poell, and Martijn De Waal. 2018. The Platform Society: Public Values in a Connective World. New York: Oxford University Press. Varis, Piia. 2015. Digital Ethnography. In The Routledge Handbook of Language and Digital Communication, ed. Alexandra Georgakopoulou and Tereza Spilioti, 55–68. London: Routledge.

CHAPTER 5

Conclusion

5.1   Stories Through the Lens of Content, Interface and Algorithmic Metrics Our analyses in the preceding chapters have shown that even if the, ever growing, presence and impact of storytelling on social media may be analysed though multiple lenses, the issue of how metrics and quantifiability intermingle with storytelling should be a key-interest, given the increasing sophistication of metrics in general and metrics dedicated to stories in particular. The case studies chosen through Chaps. 2–4 each represent different, typical instances of quantified storytelling, focusing on, respectively, the individual, the group and the platform itself. Throughout the chapters, we used the heuristic distinction between three levels of metrics—content, interface and algorithmic metrics—as a main analytical tool for teasing out the links between metrics, quantification and stories. Chapter 2 offered readings of three public Instagram profiles made by female Danish cancer patients: @jannelivsnyder66, made by Janne Hinrichsen; @kristineelleby, made by Kristine Elleby Mølbæk; and @maikenbie, made by Maiken Bie Lindegaard. The chapter more specifically explored how quantification is important for storytelling on social media through acts of self-measurement in posts shared by individual cancer patients. These self-measurements are aimed at positioning the self in a progressive time of hope and at inviting followers to support the patient’s © The Author(s) 2020 A. Georgakopoulou et al., Quantified Storytelling, https://doi.org/10.1007/978-3-030-48074-5_5

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movement towards a cure—and even to keep the teller in sync with the ideal of recovery. Self-measurements thus seem to be important navigational devices in terms of trying to process and reclaim a sense of agency during an existential crisis. The chapter also showed how this logic of ‘teleological counting’ can be disturbed by various forms of ‘frustrated counting’ when progression is stalled or by the ‘tellability crisis’ occurring when the counting process reaches its goal and the narrative contract between teller and followers must be renegotiated. The existential navigation through numerical storytelling resonates with the platformed affordances of Instagram, which are designed to extract value from the circulatory power of visually dramatic, ongoing, emblematic, brief, affectively engaging (cf. the heart button) and embodied posts (e.g. selfies) that invite followers to interact, Like and comment in empathetic and supportive ways. Chapter 2 in that way stressed not only that cancer storytelling on Instagram both shapes and is shaped by media ecologies characterized by complex subjective, affective and economic orders of worth, but also that counting practices seem to be an effective way of adapting cancer storytelling to platformed logics and constraints. Self-measurement on cancer profiles—and the affective processes it affords—might also contribute to a bio-political condition that stresses vitality, optimism and a constant personal struggle and responsibility for improvement and effectivization as the desired patient position. The chapter in that way argued that the quantified self-tracking seems to have become a crucial device for narrating, visualizing and sensing the self and body with cancer during dramatic times of transformation and crisis, but also for reproducing limited notions of culturally desirable patient behaviour. Chapter 3 turned the attention from individual, networked storytelling to the forms of collective interaction found in an extreme, yet prototypical social media public. The reading of TD’s stylistically inventive but ideologically highly controversial practices showed how the affordances of the reddit platform are crucial to the rhetoric and forms of agency taking shape here. Reddit’s segregation into autonomous subreddits facilitates what Warner (2002) calls ‘reflexive circulation’, a process the TD subreddit further accelerated by its meta-memetic strategies such as incongruous rescriptings and reflexive quantified storytelling. Reddit’s reliance on pseudonymity for its users allows for easy and non-consequential access to and participation in these forms of circulation, even when they, as in the case of TD, tend towards aggressive, anti-deliberative or toxic behaviour. Finally—and this is key in trying to understand the storytelling practices

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on TD, as well as on reddit, more generally—reddit’s implementation of numerical point scores as controllers of visibility ties positive votes to visibility and thereby to social value. The algorithmic metrics of the platform make high numbers equal high visibility both in and outside a particular subreddit; high numbers are what allows content from TD to become visible outside the subreddit. The reading showed how TD then uses this process as content for further posts, producing feedback loops of increasingly energetic interactions among the subreddit’s members and thus potentially attracting new members. The metricization of these engagements turns the numerical values of the point score into attention capital—literally by making its memes count—in that it buys the subreddit entry into the mainstream and attracts supporters, boosting the number of attendees at the platformed rally. These measurable successes then feed into quantified storytelling in the form of the telling of stories about this very process, about the viral potential and breakthrough of the numbers, generated by their rhetoric. In Chap. 4, we focused on stories as a designed feature on Instagram and Snapchat and the role of metrics in this design. We used a corpus-­ assisted analysis of online media about Instagram and Snapchat Stories and a real-time tracking of the evolution of Stories as a technical feature (technography). We also analysed Instagram Stories by Lele Pons, an Influencer with the most watched stories when Stories were introduced and remaining in the top Stories Influencers. By bringing these different analytical lenses together, we showed how the links of stories with metrics create preferential conditions (directives) for three practices in the production and engagement with stories: life-sharing-in-the-moment, audience engagement as quantified viewing and the tellers’ construction of authentic selves. As we showed, these directives prompt the telling of specific tales, specific types of audience engagement and specific modes of self-­ presentation. Put differently, they are integral to storytelling processes. The directive of sharing-life-in-the-moment leads to the posting of specific types of small stories (e.g. on the go, breaking news, behind the scenes, countdowns) that are well suited to the algorithmically favoured timeliness of postings in the here-and-now, in the everyday life. Metrics of viewing and of completion figures of stories as well as measurable aspects of the story content itself (e.g. location stickers) prompt an audience engagement that quantifies attention economy. Quantified viewing practices seem to encourage a relationship between storytellers and audiences that is based on ritual appreciation of the story and/or the storyteller (e.g. heart

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emojis), thus shunning more complex and sustained co-authorings of the story itself. Finally, the directive of constructing authentic selves becomes an integral part of an ecology of frequent posting, of ‘imperfect sharing’, that minimizes the editing and polishing time. At the same time, it privileges the sharing of the mundane and the banal, connecting teller ‘authenticity’ with a ‘spontaneous’ sharing on the spot of what is being experienced. Overall, our focus on stories as engineered features with metrics at the heart of this design showed how creative and affective processes associated with the power of stories in connecting us with others are systematically mobilized for the project of metricization of both storytellers’ and audiences’ activities. From the point of view of platform engineering, this is done by means of an ingenious and often implicit and invisible conflation (cf. commensuration) of story creativity with quantification. Stories in their entirety are measurable; stories as parts of content are measurable; engagement with stories is measurable. Tracking the analytics produced over time by this quantification separates users, rendering, for instance, Influencers more privileged than ordinary users in terms of how much of their own story metrics they can track and access. If we try and map the above key-findings of our chapters onto our three types of metrics, the first thing to note in relation to content metrics is that numbers themselves become constitutive of the stories told in several ways. One type of story lets bodily measurements, such as those related to a cancer patient’s treatment process, take on the function of events in which counting becomes telling and vice versa. Another form, reflexive on the practice of platformed storytelling itself, transforms the actions of metrics from the level of the interface into a chain of events on the level of content. We saw this in the case of the story of Stephen Sutton’s cumulative fundraising and in the cases of TD’s meta-viral stories about the explosive growth and extended outreach of their own posts. We also showed how metrics, normally associated with the interface of posts, are increasingly becoming integrated into the content and the plot of the stories, as for instance in the case of measurable and clickable location stickers, swipes and hashtags in Instagram Stories. In this way, not only can storytellers integrate metrics into how they present the plot of their stories but the engagement with different parts of the content of stories also becomes a metricized activity. The visible metrics of platform interfaces store and mark story appreciation. The numerical feedback possibilities present on Instagram and reddit (as well as on most other social media platforms) allow for (near) real-time

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assessment and valorization involving users through processes of voting, sharing and Liking. We argued that these processes and practices of quantification make some stories, lives and types of self more visible while silencing and devaluing others. A case in point was the tellability crisis encountered by a cured cancer patient who could no longer narrate her story with progressive numbers and in the form of a tracked target. In contrast, the virtual applause in the form of upvotes given to an extreme memetic experiment by a member of the online rally on The_Donald illustrated how built-in metricization processes inadvertently promote, amplify and scale up certain accounts. The metrics attached to the design of Stories on Instagram, especially the number of views, come with tiers of visibility, with certain power-users having more access to their own story analytics than others. They also ultimately shape the engagement with stories as a primarily viewable experience, which in turn affects how storytellers present themselves. All the above are examples of how (particular kinds of) stories rise to prominence or remain hidden, dependent on how they fare in relation to the metrics of the platform and its users. At the level of algorithms, (mostly) invisible metrics prove instrumental in managing users’ visibility. Striving for this visibility, tellers are under increased pressure to conform to more or less explicit directives for storytelling. As we showed, however, in the case of cancer patients, of Influencers and of a controversial political community, conformity is not a passive act but is mediated by a nexus of agentive strategic adaptations. Specifically, we showed how Influencers deploy specific genres of small stories, for example, countdowns, breaking news and on the go stories, that, on the one hand, suit the algorithmic preference for timely postings and, on the other hand, are aimed at keeping their followers engaged. Our analyses of the platforms’ storytelling functions as well as of the language produced by product managers and the industry-facing media outlets to describe them, showed that the design of story functionality is inextricably bound up with metrics. Put differently, the storytelling facilities provided by platforms are from their very inception engineered so as to be able to slice up the complex processes of telling and recipiency into countable units. Tellability as Narrative Value A recurrent theme in our investigation of stories on social media as quantified activities has been the intricate and multi-directional relationships between stories and values. In his contribution to Measure and Value

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(2012), Muniesa argues that value should neither be understood as something that people simply create by considering something as valuable nor as a property that something has. Value is neither subjective nor objective (2012). Instead, value is described as created through pragmatic actions, or valuation practices, that categorize, order, compare, rank (and thus perform) worldly elements within particular settings. Or, in the words of Adkins and Lury: ‘(I)n the operation of the activity of valuation the appraisal of the characteristics of something in terms of its value and the setting of that thing for the purpose of making it valuable merge together’ (2012, 8). This holds particularly true for social media, where, for instance, the circulatory value of a shared personal story is simultaneously linked to characteristics of the story (e.g. the surprising or interesting quality of what it tells or how it organizes time) and how it is received or hyped up by other users (e.g. by intense Liking processes). Social media measurement processes are thus not simply documenting properties of the narrative but also testing and producing narrative value, that is, what makes one story more worthy and thus more tellable than another, through constant acts of ‘not-only-representational’ measurement (Adkins and Lury 2012). Questions regarding narrative value have been routinely addressed in narrative studies under the umbrella term of ‘tellability’. Traditional ways of describing tellability have involved associating it with the type of events reported in a story, for instance, ‘events of great interest’ (Ochs and Capps 2002, 43), or with the use of ‘rhetorical skills’ that may transform the ‘seemingly prosaic’ into something ‘highly tellable’ (43). More recently, contextual accounts understand tellability as something that is neither inherent in a story nor exclusively teller-led, but instead ‘negotiated and progressively co-constructed through discursive interaction’ (Baroni 2014, 1). In Page’s terms, ‘the norms for tellability [on social media] are context sensitive, shaped by the generic contexts of social media sites and expectations derived from offline extrasituational contexts’ (2012, 200). Similarly, Shuman has argued that tellability is dependent upon pre-­ existing social norms and conventions and related to what and how an experience may be told in a given situation. Tellability is tied to ‘how experience is categorized’ (Shuman 2005, 8), with certain forms of experience being tellable only when reported in certain ways. In addition, there is a possibility for the tellers of disrupting existing rules of tellability by inventing counter-narratives and new narrative formats that go against the dominant ones. Our analyses of the Instagram and reddit cases confirm the relative, context-dependent and dynamic nature of tellability. Going

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further than that, though, we showed how the discursive formations surrounding the conceptualizations and branding of the story functions of Instagram and Snapchat are revealing of the platforms’ design that, through metrics considerations, renders certain formats tellable, such as telling-in-the-moment and constructing authenticity. The values of particular stories are therefore constantly tested, negotiated and produced on and through the platform. This happens when: • Users share something in their view tellable and are more or less immediately told whether or not this is the case (through interface metrics) • Users include numbers in their stories to make the mundane more tellable (through content metrics) • Platforms promote particular stories as more tellable than others and particular storytellers as potentially tellable per se due to their narrative track record (through algorithmic metrics). From this point of view, the measurements involved in the construction and circulation of stories can be viewed as procedures that create value at different levels, for example, through processes of categorizing and ordering that allow for comparisons and of ranking or prioritization of units (e.g. how upvoted a reddit post is compared to other posts). From the perspective of the user, we have shown how individuals engage in testing and negotiating the tellability of particular stories (e.g. in target-driven cancer narratives vs. post-cancer treatment stories). The therapeutic effects of sharing stories, we have found, was linked with them being received and confirmed as tellable through supportive commenting and Liking. We have also explored how communities such as the online rally can engage in pushing and redefining the tellability standards of particular platforms and political cultures, and also how high numbers themselves seem to be promoted as highly tellable material for stories. Furthermore, we have investigated power-users that seem to understand, follow and comply with the tellability standards of platforms in order to promote products and themselves. We have shown, in this respect, how metrics accessible to them afford them insights into how their followers actually evaluate the content they share. From a platform perspective, we have argued that tellability is produced through the directive of platforms for sharing-life-in-the-moment that defines recency and the everyday as tellable content. Mining the mundane and presenting an ordinary, non-polished self in everyday life, we saw, is a

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hallmark of the directive for authenticity. This—in many ways, staged— authenticity, which in the case of Influencers blurs the boundaries between the ordinary self and the promotion of products, has rendered stories as ideal vehicles for advertising embedded in platforms. Multivalent Platforms and the Problem of Public Value We set out with the intention to steer clear of simplistic, either/or, accounts of technological determinism or user agency. As our analyses show, the picture of what forms of values are produced and how they come to matter is more complicated and diverse, calling for a multivalent approach to social media communication. The concept of ‘multivalence’ has been used in media and sociological research in order to highlight how social media are designed to produce multiple forms of value simultaneously (Gerlitz 2016). When a cancer patient shares a post on Instagram on their insecurities of how their treatment is working—and it is shared further by their followers—numerous forms of value are potentially enacted at the same time: • affective-psychological values linked to the act of narration. • social values linked to collective support and empathy. • attention-circulation value linked to pushing the heart button, which registers the response but also distributes the content further in the network (Gerlitz and Helmond 2013). • economic value linked to various forms of datafication of user behaviour and so on. By focusing on ‘multivalence’ when investigating media participation, it is possible to stress (a) how media use on social media platforms is engaged in multiple forms of value production; and (b) that platforms in themselves are participatory agents that turn various forms of media practices into value on different registers (Marres 2011). The focus on the co-articulation of personal, social, economic and narrative value production, however, also motivates a range of new fundamental questions. For instance: who exactly gets what out of turning social relations and ‘connectedness’ into economically valuable data or ‘connectivity’ and whose interests are supported through this transformation (van Dijck 2013)? Following the research of, for example, van Dijck, Poell and Waal, we must therefore complement the focus on multivalence with an interest in

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‘public value’, in order to be able to ask more basic or political questions such as: to what extent do the multiple values created by social media platforms support or disturb ‘the common good’? Important examples of public values that are, in the view of van Dijck, Poell and Waal, often challenged due to the corporate platformization of society are values such as privacy, accuracy, safety, consumer protection, fairness, equality, solidarity, accountability, transparency and democratic control (van Dijck et al. 2018). By understanding social media as designed for multivalence and for maintaining an idea of vital public values, it becomes possible to approach quantified storytelling as an ambivalent process of valuation and tellability production. Chapter 2 demonstrated how content metrics intertwine with processes of therapy and support during illness, but also how these metrics risk supporting a widespread understanding of a ‘tellable illness narrative’ as being a narrative about hope and progress. Chapter 3 illustrated how quantified storytelling produces social mobilization through processes of collectively ranked tellability, but also its toxic potentials (and non-value) for what has traditionally been understood as tellable narratives in political culture at large (e.g. news from inside the democratic political system). Chapter 4 stressed economic valuation criteria underlying the design of stories and showed how affective, creative and relational aspects of stories are co-opted by platforms in their push for metricizable and datafiable postings. In addition, particular types of teller and storytelling format are valued higher than others by the platform. This is attested to in the access that highly valued tellers have to otherwise invisible metrics that allow them to improve future traction and revenues. Reactive Agency? Overall, we showed how narrative values are produced and negotiated in a constant tension between agentive practices of storytelling, sharing and responding, and platform logics that organize, extract value from and direct users towards particular types of storytelling activities by means of quantification. While it is a relatively uncontroversial claim that multiple forms of value are produced simultaneously through quantified storytelling, the overall cultural effects or value of this turn to metricization of stories is more difficult to pin down. Are metrics supporting a neoliberal push towards effectivization, automated surveillance (Andrejevic 2019) of the mundane and the instrumentalization of human attention in evermore complex ways? Or, should metricization be understood as an everyday

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practice, where users navigate and engage with numbers and numbering technologies as yet another cultural tool for sense-making? Even if we accept that users ultimately repurpose metrics and other affordances for stories for local, interactional goals, does this have the power to ultimately undermine the platforms’ push for datafication and their commoditization of stories? And what is the role of the media-afforded processes of amplification and scalability in this process? How does their potential for making specific types of stories and storytelling practices widely available and visible affect any user resistances? The answers to the above questions are, as we see it, to be located in the ever-evolving tension between platform structuration and user agency that we have continuously stressed throughout the chapters. The spread of the ‘algorithmic imaginary’ (Bucher 2018), increased political awareness of data security and rising political demand for making the ‘Big Five’ accountable underlines how a space for agency and public contestation is potentially taking shape. At the same time, data scandals and the lack of obvious alternatives to the opaque regime of the ‘Big Five’ seem to stress the impossibility of escaping the pervasive quantification of everything, everybody and every moment. Maybe we are, as argued by Velkova and Kaun, therefore living in the midst of a media culture where agency is best understood as ‘reactive’ or based on ‘media practices of repair’. These can be defined as ‘tactics to correct existing shortcomings within algorithmic culture rather than by producing alternative pathways’ (Velkova and Kaun 2019, 2). Such a reactive agency would imply not only that the current quantification is unavoidable but also that measurements can be used for multiple purposes and sometimes even to instrumentalize algorithms for individual and collective purposes. Quantification on social media is pervasive; it is saturated by the drive to extract knowledge and value from every dimension of (online) life, but it is also mundanely (re)worked and (re)created by people as part of making sense of and inhabiting digital worlds.

References Adkins, Lisa, and Celia Lury. 2012. Introduction: Special Measures. In Measure and Value, ed. Lisa Adkins and Celia Lury. Oxford: Wiley-Blackwell. Andrejevic, Mark. 2019. Automated Media. New York: Routledge. Baroni, Raphaël. 2014. Tellability. In The Living Handbook of Narratology, ed. Peter Hühn et al. Hamburg: Hamburg University. http://www.lhn.uni-hamburg.de/article/tellability [view date: 12 Feb 2019].

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Bucher, Taina. 2018. IF…THEN. Algorithmic Power and Politics. Oxford: Oxford University Press. Dijck, Van, Thomas Poell José, and Thomas de Waal. 2018. The Platform Society. Public Values in a Connective World. New York: Oxford University Press. Gerlitz, Carolin. 2016. What Counts? Reflections on the Multivalence of Social Media Data. Digital Culture and Society 2 (2): 19–38. Gerlitz, Carolin, and Anne Helmond. 2013. The Like Economy. New Media and Society 15 (8): 1348–1365. Marres, Noortje. 2011. The Costs of Public Involvement: Everyday Devices of Carbon Accounting and the Materialization of Participation. Economy and Society 40 (4): 510–533. Muniesa, Fabian. 2012. A Flank Movement in the Understanding of Valuation. In Sociological Review Monograph Series, ed. Lisa Adkins and Celia Lury. Oxford: Wiley-Blackwell. Ochs, Elinor, and Lisa Capps. 2002. Living Narrative. Creating Lives in Everyday Storytelling. Cambridge: Harvard University Press. Page, Ruth. 2012. Stories and Social Media: Identities and Interaction. New York and London: Routledge. Shuman, Amy. 2005. Other People’s Stories. Urbana and Chicago: University of Illinois Press. Van Dijck, José. 2013. The Culture of Connectivity. New  York: Oxford University Press. Velkova, Julia, and Anne Kaun. 2019. Algorithmic Resistance: Media Practices and the Politics of Repair. Information, Communication & Society. Warner, Michael. 2002. Publics and Counterpublics. Public Culture 14 (1): 49–90.

Index1

A Affect affection economy, 119, 123, 124 affective crowd, 84 affective economy/ economies, 24, 34 affective engagement, 11, 84 affective feedback loop, 40 Affordances, 14, 16–18, 20, 23, 24, 34–36, 51–54, 62–68, 74, 79, 84, 86, 87, 95, 97, 99–103, 106, 112, 113, 120, 121, 125, 134, 142 Agency, 8, 10, 11, 17–18, 32, 43, 45, 53, 126, 134, 140–142 Algorithmic metrics, 9, 21, 64, 65, 68, 83–86, 97, 98, 105, 125, 133–142 Algorithm(s), 9, 10, 22, 25n2, 64–66, 86, 87n3, 100, 108, 127n14, 128n25, 137, 142 Alignment, 40, 41, 43, 47, 49, 54

Alt-right, 69, 87n4, 88n10 Anonymity, 62–64, 66, 67 Assessment, 1, 64, 97, 111, 124, 137 Attention economy, 31, 112, 125, 135 Audience engagement, 24, 96, 98, 112–119, 123–125, 135 Authenticity, 98, 119–124, 128n23, 128n24, 136, 139, 140 authentic self/selves, 24, 123–125, 135, 136 B Banal imaging, 37 Breaking news, 14, 16, 52, 103, 112, 135, 137 C Cancer, 19, 20, 31, 32, 34–36, 38–44, 48, 49, 51–54, 95, 133, 134, 136, 137, 139, 140

 Note: Page numbers followed by ‘n’ refer to notes.

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INDEX

Collocations, 103, 120, 122, 127n11 Commensuration, 118, 119, 125, 136 Commodification, 5 Community online community, 62, 69–72, 84, 87n5 virtual community, 87n5 Content metrics, 21, 22, 31, 43, 78, 82, 127n14, 136, 139, 141 Corpus analysis, 19, 104, 105, 119, 126n10 Corpus/corpora, 20, 104–110, 117–120, 122, 126n9, 126n10, 127n15, 128n24 Countdown, 21, 40, 112, 123, 135, 137 Counterpublic, 24, 62, 69, 70, 72, 79–84, 86 Counting, 2–4, 6, 7, 22, 23, 31, 32, 36, 40–42, 44–46, 51–54, 67, 134, 136 frustrated counting, 44–46, 134 Creativity, 114, 117, 119, 122, 136 Critical discourse analysis, 101 Critical moment, 102, 103 Crowd online crowd, 62, 69, 71, 72, 79, 83 affective crowd, 84 Cumulative counting, 32 Curation, 5, 15, 102, 114 D Datafication, 5, 11, 25, 35, 98, 115, 140, 142 Desired narrative, 47–51 Digital architecture, 5 Digital ethnography, 100 Directives, 3, 24, 95–126, 135–137, 139, 140

Discourse(s), 13, 15, 17, 18, 20, 24, 25, 54, 70, 72, 73, 78, 79, 82–84, 88n8, 101–103, 120 Disruption, 20, 22–24, 31 biographical disruption, 33 Distribution, 2, 4, 16–18, 23, 64, 84, 104 E Ego-Media, 104, 106, 108–110 Emblematic, 23–25, 41, 51, 53, 75, 134 Emoji(s), 40, 47, 97, 111, 124, 136 Entanglement, 125 Entextualized, 42 Ephemerality, 106, 108 F Facebook, 2, 5, 7, 11, 16, 20, 22, 23, 32, 34, 36, 37, 55n5, 63, 65, 68, 95, 99, 102–104, 118, 119, 126n5, 127n14 Fictionality, 15, 88n8 Filters, 99, 120, 121 Future, 8, 10, 21, 23, 25, 32, 33, 35, 43, 45, 46, 50, 51, 53, 54, 66, 77, 105, 141 G Genre, 14–17, 19, 55n4, 127n13, 137 H Hashtag(s), 17, 18, 37, 71, 111, 113, 118, 123, 136 Hope, 18, 32, 38, 40–43, 47, 51, 54, 78, 83, 133, 141

 INDEX 

I Illness, 4, 17, 22, 31–35, 37–39, 43–49, 51–54, 141 Imperfect sharing, 120, 128n22, 136 Influencers, 1, 20, 22, 23, 37, 38, 97, 98, 102, 105–106, 111, 112, 114, 119, 121–125, 127n12, 127n14, 135–137, 140 Instafame, 37 Instagram Instagram posts, 19, 38 Instagram Stories, 20, 96, 97, 104, 112, 114, 122, 124, 127n21, 135, 136 Interaction, 1, 4, 5, 12, 18, 23–25, 47, 50, 52, 61, 63–68, 70, 72, 75, 77, 84, 87n5, 98, 99, 105, 114, 117, 124, 125, 126n4, 134, 135, 138 identities-in-interaction, 13 Interface metrics, 21, 22, 24, 48, 49, 64, 65, 67, 68, 72, 82, 84, 85, 97, 105, 139 (In)visibility, 22, 38, 98, 112–115, 125 K Keywords, 103, 104, 106, 116, 119 L Life-logging, 8, 52 M Master plot, 23, 31, 33, 42, 47, 48, 51 Measure affective measure, 10, 42 performative measure, 47–53

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Measurement, 2–11, 19, 21–23, 25, 31, 32, 35, 36, 41, 42, 44, 45, 52, 54, 64, 113, 136, 138, 139, 142 Mediation, 10, 17 Meme, 61–87, 135 meme magic, 74, 75, 80, 81 Memetic, 23, 68, 77, 78, 85, 137 meta-memetic, 75–80, 83, 134 Metaphor(s), 31, 33 Metricization, 1, 4, 5, 12, 19–21, 62, 85, 95, 98, 113, 115–119, 122, 125, 135–137, 141 Metricized activities, 102, 136 (Micro)-celebritization, 123 Mobilize, 2, 123, 136 Moment sharing the moment, 102, 103, 106 showing the moment, 103 (Multi)-authorship, 16 Multivalence, 11, 140, 141 N Narrative illness narrative, 33–37, 43, 47, 141 interlocking, 42 narrative stancetaking, 14 narrative value, 137–141 personal narrative, 15 restitution narrative, 33, 42, 44, 46–48, 50, 53 Narratology, 12–16 Networked photography, 37 O Online media, 104, 105, 124, 135 Orders of worth, 53, 134

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P Participation, 11, 13, 16–18, 70, 101, 134, 140 Performativity, 13 Personalization, 22, 35 Platform, 1–5, 7, 9–12, 16–21, 23, 24, 31, 34–39, 51, 52, 54, 62–68, 74, 75, 79–81, 84–87, 88n10, 95, 96, 98, 99, 101, 105, 115, 120, 126n1, 127n16, 133–137, 139–142 Plot, 2–4, 14, 18, 25, 78, 83, 98, 136 Positioning, 8, 48, 53, 69, 100, 133 Positivity, 42, 47–53 Practices communicative practices, 85, 87, 95, 97, 102, 105–106 posting practices, 98 Probability, 43 Public, 5, 14, 15, 17, 18, 32, 34, 38, 40, 48, 61, 62, 67, 68, 70–72, 77, 79, 80, 82–84, 86, 120, 133, 134, 140–142 Q Quantification, 1, 3–7, 11, 12, 19, 21–24, 31, 34–37, 84, 97, 98, 115–117, 119, 124, 125, 133, 136, 137, 141, 142 Quantified self, 21 Quotes, 40, 76, 77 R Rally, 62, 69, 72, 73, 76, 81, 85, 135, 137, 139 Recovery, 53, 54, 134 Reddit redditor, 63, 64, 67, 75, 80, 82 subreddit, 19, 61–70, 72–74, 78, 79, 81, 82, 84–86, 134, 135

the_Donald (TD), 19, 61, 62, 68–73, 75–80, 82–86, 88n10, 134–137 Reflexive, 23, 35, 62, 68, 70, 79, 83, 84, 99, 134, 136 Reportable, 32, 42, 53 Rescripting, 23, 68, 78, 81, 85 incongruous, 62, 78, 81, 84, 134 Rhetoric, 4, 15, 17, 61, 69, 78, 79, 81, 83, 85, 106, 114, 117, 123, 127n16, 134, 135 Ritual appreciation, 47, 124, 125, 135 S Score, 1, 3, 9, 21, 22, 24, 35, 36, 47, 48, 63–65, 67, 72, 74, 82–86, 105, 121, 135 Selfie(s), 35, 37, 41, 44, 48, 49, 53, 55n2, 103, 120, 123, 124, 127n21, 134 Self-measurement, 8, 9, 21, 35, 36, 38, 40, 42–44, 52–54, 133, 134 Self-presentation, 4, 98, 119–124, 135 Self-tracking, 7–8, 21, 23, 46, 52, 54, 134 Sharing life in the moment, 14, 98, 106–112, 120, 123, 125, 135, 139 Small stories, 14, 16, 22, 50, 55n4, 74, 78, 82, 100, 103, 108, 123, 125, 135, 137 Small stories research, 13, 14, 102 Snapchat, 2, 4, 20, 24, 95–97, 99, 102, 104, 113, 117, 120, 124, 127n17, 127n21, 128n22, 135, 139 Snapchat Stories, 20, 24, 95–97, 102, 104, 113, 117, 120, 124, 127n21, 128n22, 135, 137, 139 Stickers, 113, 121, 123, 135, 136

 INDEX 

Story chaos story, 33 quest story, 33 restitution story, 33 story responses, 21, 62 Storytelling digital storytelling, 17, 25n3 reflexive quantified, 23, 62, 83, 134 Structuration, 10, 11, 34, 142 Supportive disalignment, 50 T Technography, 103, 135 Teleological counting, 22, 32, 40–43, 45, 134 Tellability, 4, 13, 16, 18, 51, 52, 137–141 tellability crisis, 23, 47–53, 134, 137 Teller, 3, 4, 13, 14, 22–24, 32, 42, 43, 48, 52–54, 55n4, 98, 117, 119–124, 134–138, 141 Telos, 32, 52, 53 Temporality, 12, 43, 78 Temporal progression, 32, 53 Timeliness, 87n3, 108, 112, 125, 127n14, 135

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Tools, 6–8, 11, 21, 23, 25, 37, 85, 97, 98, 106, 113–115, 117, 119–121, 123, 126, 127n11, 128n22, 133, 142 Tracking, 4, 7, 8, 22, 35, 53, 95, 97, 102–103, 105, 113, 114, 127n21, 135, 136 Treatment, 2, 31, 32, 35, 36, 39–47, 50–53, 54n2, 136, 139, 140 V Values, 2–4, 9–11, 23, 32, 43, 49, 53, 54, 63–66, 72, 82, 84–86, 87n4, 97, 98, 100–103, 105, 123, 125, 127n15, 134, 135, 137–142 Vanity metrics, 7, 36, 114 Viewable, 124, 137 Viewing, 96, 113, 115, 118, 122, 123, 125, 135 quantified viewing, 24, 98, 112–119, 124, 135 Viral, 17, 85, 135 Visuality, 35, 37, 123 Vote upvote, 63, 64, 66, 75, 79, 80, 82, 137 voting pattern, 86