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Regimes of recognition on algorithmic media

Jacobsen, Benjamin N (2021) 'Regimes of recognition on algorithmic media.', New Media & Society .

Abstract

This article examines ways in which people are seen, recognised, and made to matter by social media platforms. Drawing on Louise Amoore’s notion of ‘regimes of recognition’, I argue that social media platforms can be conceptualised as increasingly powerful arbiters of recognisability, determining the conditions of possibility of how people are seen and come to matter. Through an analysis of Twitter’s saliency detection algorithm, which automatically crops images uploaded to the platform, the article highlights how social media platforms participate in producing novel modes of recognisability, that is, conditions by which people are rendered visible and invisible within or by the platform. Moreover, the article highlights how regimes of recognition on algorithmic media shape people’s parameters of attention and perception more generally through what I call the automatic production of ‘consistent’ lines of sight. Ultimately, the article seeks to highlight how the notion of recognition is increasingly arbitrated in and through algorithmic media and how this is fraught with political issues and tension. As such, there is an ongoing need to critically examine the power of social media to render people visible and invisible.

Item Type:Article
Full text:(VoR) Version of Record
Available under License - Creative Commons Attribution 4.0.
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1177/14614448211053555
Publisher statement:This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages
Date accepted:28 September 2021
Date deposited:20 January 2022
Date of first online publication:26 October 2021
Date first made open access:20 January 2022

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