How metrics matter: Mapping reactions to social media metrics in the public issues of Covid-19 misinformation and users' health and well-being

Social media metrics such as like counts or engagement rates have become a critical issue in our contemporary datafied societies (Gerlitz & Helmond, 2013; Marres, 2017). Content creators, conspiracy and far-right groups, artists and activists, under contrasting agendas, are unfolding diverse tactics to game the metrics and intervene in the (in)visibility, reputation and value of certain contents and accounts on social media platforms (Brunton & Nissenbaum, 2015; Bucher, 2018; Cotter, 2018; Marwick & Lewis, 2017; van der Nagel, 2018). These tactics indicate the ubiquity in social media of forms of 'reactivity' or the idea that 'measures elicit responses from people who intervene in the objects they measure' (Espeland and Sauder, 2007, p. 2). Reactivity in social media has been commonly framed as 'inauthentic behaviour', 'sources of bias', or 'fraud'. For this reason, multiple platforms have developed legal policies, algorithmic systems and interfaces redesigns to combat 'fake engagement' and control reactivity. However, reactive practices are not always unexpected, but can also be a deliberately designed achievement by platforms (Gerlitz & Lury, 2014). This suggests that, in certain situations, reactivity is not only accepted, but is an effect that is built into the design of social media metrics, but in others, it becomes problematic and characterized as "abusive" or "harmful" to the maintenance of a healthy social media environment.
This doctoral research project will move established understandings of reactivity to social media metrics as necessarily problematic forms of malicious manipulation and methodological bias, in order to investigate how they come to be qualified as problematic in the first place. Drawing upon the work of interrelated fields of Digital Sociology, Science and Technology Studies and Sociology of Quantification, my aim is to inquiry into the distinctive problems that emerge from reactivity to metrics in social media. This project interrogates then the following: how, for whom, and for what ends our relations with metrics in social media becomes a matter of concern? I will explore this question in two substantive areas: a) the amplification of Covid-19 misinformation or how metric reactivity has contributed to the reach of conspiracy and anti-vaccine groups, b) the effects of social media metrics on health and well-being of users and contemporary experiments to mitigate these effects.
I will conduct a multi-sited digital ethnography (Hine, 2015) that includes a cross-platform analysis with digital methods (Marres, 2015; Rogers, 2013) to map the two selected public issues and the forms of evidence, demonstration, and intervention put forward to address reactivity in social media; (b) participant observation and semi-structured interviews with content creators involved in reactive practices in social media to modify their algorithmic visibility, as well as with engineers and designers dedicated to the detection and prevention of metrics manipulation; (c) a review of secondary materials about experiments and controversies around social media metrics such as public media, NGO reports, marketing agencies brochures and policy literature; (d) the development of prototypes or digital probes to elicit reactions to social media metrics within the research itself, in a more speculative and practice-based line of inquiry.
This research project will contribute to Digital Media Studies and Computational Social Science by introducing classical sociological debates about measurement in the study of social media data. It proposes to rethink reactive practices as situations that manifest the "natively artificial" quality of social media data (Marres, 2017; Marres & Gertliz, 2018) that emerge from the lively entanglements between measuring devices and measured objects.