The DOI matches its Crossref record; 45 of the 46 references it cites were found in a registry or an index.
Managing visibility on YouTube through algorithmic gossip
Open accessAbstract
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.
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“The emotional labor catering to advertisers and audiences' feeds into metrics that evaluate the creative work visibility (Bishop, 2019).”
From ‘Traffic rewards’, ‘algorithmic visibility’, and ‘advertiser satisfaction’: How Chinese short-video platforms cultivate creators in stages (2024) · cites this paper as Bishop, 2019
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“Previous literature has already identified A/B testing (Cotter 2019), algorithmic gossip (Bishop 2019), and leveraging algorithms (Kellogg et al. 2020) as coping mechanisms.”
From Content Creators Between Platform Control and User Autonomy: The Role of Algorithms and Revenue Sharing (2023) · cites this paper as Bishop 2019
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Citations
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“So far, YouTube beauty communities have been examined as they curate microcelebrity (Senft, 2008) and perform entrepreneurship (Duffy, 2017), and intimately connect with their followers (García-Rapp, 2017).”
Background
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“Algorithmic precar-ity was both the highest-scoring and least dispersed survey dimension and the most widely shared theme, with 60% of interviewees describing fatalistic rather than resis - tant adaptation, consistent with Bishop’s ( 2018 , 2019) accounts of algorithmic opac - ity.”
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Bassett, K. (2026) · Journal of Cultural Economy · doi:10.1080/17530350.2026.2733392
Metadata
- Authors
- Bishop, S.
- Affiliations
- King's College London (GB)
- Corresponding author
- Bishop, Sophie
- ORCID
- Bishop, Sophie
- Venue
- New Media & Society
- Publisher
- SAGE Publications
- Published
- 2019-06-15
- Volume
- 21
- Issue
- 11-12
- Pages
- 2589-2606
- ISSN
- 1461-4448 (ISSN-L)
- 1461-7315
- OpenAlex
- W2951551356
- Cited by
- 535
- References
- 46
- Citations by year
- 2026: 131 · 2025: 106 · 2024: 91 · 2023: 83 · 2022: 60 · 2021: 46 · 2020: 16 · 2019: 2
- FWCI
- 54.16
- Type
- journal article
- Language
- en
- Open access
- green
- kclpure.kcl.ac.uk
- Locations
- New Media & Society (publishedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- Topics
- Social Sciences › Gender Studies › Gender, Feminism, and Media
- Social Sciences › Communication › Media and Digital Communication
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Keywords
- beauty vloggers, YouTube, algorithmic visibility, recommendation algorithms, social networking sites, algorithmic knowledge
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