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

Managing visibility on YouTube through algorithmic gossip

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Bishop, Sophie·2019·New Media & Society

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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  • Emotional labor aimed at advertisers and audiences enters the metrics that assess creative work visibility.

    “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

    The Methodology section describes a vlogger’s public appeal to fans as “visibility labour” and identifies subscribers and views as visibility metrics (pages not provided). The Introduction also discusses the emotional stakes of maintaining visibility. But these passages do not establish that emotional labour catering to advertisers and audiences feeds into the metrics that evaluate creative work. (LLM, conf=0.82)

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  • Previous literature has identified A/B testing, algorithmic gossip, and leveraging algorithms as coping mechanisms.

    “Previous literature has already identified A/B testing (Cotter 2019), algorithmic gossip (Bishop 2019), and leveraging algorithms (Kellogg et al. 2020) as coping mechanisms.”

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

Research works printed but not linked: 5

  1. Abelove, H. (2003). Deep gossip. Minneapolis: University of Minnesota Press.
  2. Abidin, C. (2017). # familygoals: Family Influencers, Calibrated Amateurism, and Justifying Young Digital Labor. Social Media+ Society, 3(2), 2056305117707191.
  3. Andrejevic, M. (2009). Exploiting YouTube: contradictions of user-generated labor. In P. Snickars & P. Vonderau (Eds.), The YouTube Reader (Vol. 413). Retrieved from http://forskning.blogg.kb.se/files/2012/09/YouTube_Reader.pdf#page=204
  4. Meehan, E. R. (1986). Meehan, Conceptualizing Culture as Commodity. Critical Studies in Mass Communication, 3(4), 448-457. https://doi.org/15295038609366675
  5. Sandvig, C., Hamilton, K., Karahalios, K., & Langbort, C. (2014). Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms. Paper Presented to "Data and Discrimination: Converting Critical Concerns into Productive Inquiry," a Preconference at the 64th Annual Meeting of the International Communication Association. May 22, 2014; Seattle, WA, USA., 23. Retrieved from https://pdfs.semanticscholar.org/b722/7cbd34766655dea10d0437ab10df3a127396.p

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Authors
Bishop, S.
Affiliations
King's College London (GB)
Corresponding author
Bishop, Sophie
Venue
New Media & Society
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
Locations
  • New Media & Society (publishedVersion)
  • Research Portal (King's College London) (submittedVersion, other-oa)
Topics
  • Social Sciences › Gender Studies › Gender, Feminism, and Media
  • Physical Sciences › Computer Science › Computer Networks and Communications › 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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