Managing visibility on YouTube through algorithmic gossip
By Sophie Bishop. New Media & Society, 2019
460 citations recorded by the source corpus.
Beauty vloggers’ feminised outputs often position them outside of traditional spheres of technical expertise, however, their strategic management of algorithmic visibility makes them an illuminating source of algorithmic knowledge. I draw from an ethnography of beauty vloggers and industry stakeholders to study the collaborative and directive processes used to formulate and sustain algorithmic expertise – algorithmic gossip. Algorithmic gossip is defined as communally and socially informed theories and strategies pertaining to recommender algorithms, shared and implemented to engender financial consistency and visibility on algorithmically structured social media platforms. Gossip is productive: community communication and talk informs and supports practices such as uploading frequently and producing feminised beauty content to perform more effectively on YouTube. Taking gossip seriously can present a valuable resource for revealing information about how algorithms work and have worked, in addition to revealing how perceptions of algorithms inform content production.
Subfields: Clinical Psychology, Gender Studies, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/300eba4cb0120e606ebe7efbc31da1aa55d8d6b8
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Citations in the corpus
- Experiencing Algorithms: How Young People Understand, Feel About, and Engage With Algorithmic News Selection on Social Media (2021, background): “This matters because much previous work on algorithmic literacy pertains to subgroups that are already relatively digitally literate, such as algorithmic activists (Velkova & Kaun, 2019), web shop owners (Klawitter & Hargittai, 2018), and social media influencers (Bishop, 2019; Cotter, 2019).”