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Computing the everyday: social media as data platforms

Alaimo, Cristina and Kallinikos, Jannis (2017) Computing the everyday: social media as data platforms. The Information Society, 33 (4). pp. 175-191. ISSN 0197-2243

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Identification Number: 10.1080/01972243.2017.1318327

Abstract

We conceive social media platforms as sociotechnical entities that variously shape user platform involvement and participation. Such shaping develops along three fundamental data operations that we subsume under the terms of encoding, aggregation, and computation. Encoding entails the engineering of user platform participation along narrow and standardized activity types (e.g., tagging, liking, sharing, following). This heavily scripted platform participation serves as the basis for the procurement of discrete and calculable data tokens that are possible to aggregate and, subsequently, compute in a variety of ways. We expose these operations by investigating a social media platform for shopping. We contribute to the current debate on social media and digital platforms by describing social media as posttransactional spaces that are predominantly concerned with charting and profiling the online predispositions, habits, and opinions of their user base. Such an orientation sets social media platforms apart from other forms of mediating online interaction. In social media, we claim, platform participation is driven toward an endless online conversation that delivers the data footprint through which a computed sociality is made the source of value creation and monetization.

Item Type: Article
Additional Information: © 2017 The Authors
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HE Transportation and Communications
Sets: Departments > Management
Date Deposited: 15 Jun 2017 15:48
Last Modified: 21 Sep 2017 14:42
URI: http://eprints.lse.ac.uk/id/eprint/81432

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