Controversies surrounding social media platforms have provided opportunities for institutional reflexivity amongst users and regulators on how to understand and govern platforms. Amidst contestation, platform companies have continued to enact projects that draw upon existing modes of privatized governance. We investigate how social media companies have attempted to achieve closure by continuing to set the terms around platform governance. We investigate two projects implemented by Facebook (Meta)—authenticity regulation and privacy controls—in response to the Russian Interference and Cambridge Analytica controversies surrounding (...) the 2016 U.S. Presidential Election. Drawing on Goffman’s metaphor of stage management, we analyze the techniques deployed by Facebook to reinforce a division between what is visible and invisible to the user experience. These platform governance projects propose to act upon _front-stage data relations:_ information that users can see from other users—whether that is content that users can see from “bad actors”, or information that other users can see about oneself. At the same time, these projects relegate _back-stage data relations_—information flows between users constituted by recommendation and targeted advertising systems—to invisibility and inaction. As such, Facebook renders the user experience actionable for governance, while foreclosing governance of back-stage data relations central to the economic value of the platform. As social media companies continue to perform platform governance projects following controversies, our paper invites reflection on the politics of these projects. By destabilizing the boundaries drawn by platform companies, we open space for continuous reflexivity on how platforms should be understood and governed. (shrink)

The proliferation of digital data has been the impetus for the emergence of a new discipline for the study of social life: ‘computational social science’. Much research in this field is founded on the premise that society is a complex system with emergent structures that can be modeled or reconstructed through digital data. This paper suggests that computational social science serves practical and legitimizing functions for digital capitalism in much the same way that neoclassical economics does for neoliberalism. In recognition (...) of this homology, this paper develops a critique of the complexity perspective of computational social science and argues for a heterodox computational social science founded on the meta-theory of critical realism that is critical, methodological pluralist, interpretative and explanative. This implies diverting computational social science’ computational methods and digital data so as to not be aimed at identifying invariant laws of social life, or optimizing state and corporate practices, but to instead be used as part of broader research strategies to identify contingent patterns, develop conjunctural explanations, and propose qualitatively different ways of organizing social life. (shrink)

Recognizing that many of the modern categories with which we think about people and their activities were put in place through the use of numbers, we ask how numbering practices compose contemporary sociality. Focusing on particular forms of algorithmic personalization, we describe a pathway of a-typical individuation in which repeated and recursive tracking is used to create partial orders in which individuals are always more and less than one. Algorithmic personalization describes a mode of numbering that involves forms of de- (...) and re- aggregating, in which a variety of contexts are continually included and excluded. This pathway of a-typical individuation is important, we suggest, to a variety of domains and, more broadly, to an understanding of contemporary economies of sharing where the politics of collectivities, ownership and use are being reconfigured as a default social. (shrink)