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
Cites
Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
Lebovits, H. (2018) · Public Integrity · doi:10.1080/10999922.2018.1511671 · Cited by 3,320
Algorithms of Oppression: How Search Engines Reinforce Racism
Noble, S. U. (2020) · doi:10.2307/j.ctt1pwt9w5 · Cited by 2,709
The platformization of cultural production: Theorizing the contingent cultural commodity
Nieborg, D. B., & Poell, T. (2018) · New Media & Society · doi:10.1177/1461444818769694 · Cited by 1,530
Thinking critically about and researching algorithms
Kitchin, R. (2016) · Information Communication & Society · doi:10.1080/1369118x.2016.1154087 · Cited by 1,471
The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms
Bucher, T. (2016) · Information Communication & Society · doi:10.1080/1369118x.2016.1154086 · Cited by 1,420
Abidin, C. (2016) · Media International Australia · doi:10.1177/1329878x16665177 · Cited by 1,250
Status update: celebrity, publicity, and branding in the social media age
(2014) · Choice Reviews Online · doi:10.5860/choice.51-5062 · Cited by 1,165
Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram
Cotter, K. (2019) · New Media & Society · doi:10.1177/1461444818815684 · Cited by 1,025
Algorithms as culture: Some tactics for the ethnography of algorithmic systems
Seaver, N. (2017) · Big Data & Society · doi:10.1177/2053951717738104 · Cited by 1,010
(Not) Getting Paid to Do What You Love: Gender, Social Media, and Aspirational Work
Duffy, B. E. (2017) · Yale University Press · doi:10.12987/yale/9780300218176.001.0001 · Cited by 931 · cited 3×
“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
Research works printed but not linked: 5
- Abelove H, 2003, Deep Gossip
- Abidin C, 2017, Social Media+ Society, 3, 707191
- 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
- 10.18574/nyu/9781479833641.001.0001 · DOI
- 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
Cited by
Sorted by citations
Mapping Internet Celebrity on TikTok: Exploring Attention Economies and Visibility Labours
Abidin, C. (2020) · Cultural Science Journal · doi:10.5334/csci.140 · Cited by 564
Swart, J. (2021) · Social Media + Society · doi:10.1177/20563051211008828 · Cited by 381
“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).”
BackgroundDuffy, B. E., & Meisner, C. (2022) · Media Culture & Society · doi:10.1177/01634437221111923 · Cited by 441
“Following from writings on algorithmic imaginaries (Bishop, 2019; Bucher, 2017), we acknowledge the interrelated nature of user perceptions and practices , particularly in cases where the material realities of software are belied by their opacity (Natale, 2019: 713).”
InfluentialThe ethnographer and the algorithm: beyond the black box
Christin, A. (2020) · Theory and Society · doi:10.1007/s11186-020-09411-3 · Cited by 327
“…example, one can take the case of content creators and “ influencers ” producing and sharing online content such as videos, pictures, and blog posts on YouTube, Instagram, Twitter, TikTok, and so on (Marwick 2013; Duffy and Hund 2015; Duffy 2017; Bishop 2019; Stuart 2020; Burgess and Green 2018).”
BackgroundThe Nested Precarities of Creative Labor on Social Media
Duffy, B. E., Pinch, A. C., Sannon, S., & Sawey, M. (2021) · Social Media + Society · doi:10.1177/20563051211021368 · Cited by 309
“Nolan explained why he was also creating content on sites like YouTube and Instagram: You’ve probably seen on the news too about the potential TikTok ban, everything happening with the app . . . [It has] given me a wake-up call to try and not focus so heavily on one platform, even though I’m doing so well, and to try…”
BackgroundResultInfluential
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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