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Cited by 535Gender, Feminism, and MediaMedia and Digital CommunicationDigital Economy and Work Transformation

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 access
Bishop, Sophie·2019·New Media & Society
DOI 10.1177/1461444819854731
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Abstract

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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1 of the 46 references couldn’t be matched to a known paper.

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  1. Abelove H, 2003, Deep Gossip
  2. Abidin C, 2017, Social Media+ Society, 3, 707191
  3. Andrejevic M (2009) Exploiting YouTube: contradictions of user-generated labor. In: Snickars P, Vonderau P (eds.) The YouTube Reader (Vol. 413). Available at: http://forskning.blogg.kb.se/files/2012/09/YouTube_Reader.pdf#page=204
  4. 10.18574/nyu/9781479833641.001.0001 · DOI
  5. Sandvig C, Hamilton K, Karahalios K, et al. (2014) Auditing Algorithms: research Methods for Detecting Discrimination on Internet Platforms. In: Proceedings of the ‘Data and discrimination: converting critical concerns into productive inquiry’, a preconference at the 64th annual meeting of the international communication association, Seattle, WA, 22 May 2014. Available at: https://pdfs.semanticscholar.org/b722/7cbd34766655dea10d0437ab10df3a127396.pdf

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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
DOI
10.1177/1461444819854731
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
Licence
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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