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Content Creation within the Algorithmic Environment: A Systematic Review

Author

Listed:
  • Yin Liang

    (Newcastle University Business School, UK)

  • Jiaming Li

    (Birmingham Business School, UK)

  • Jeremy Aroles

    (University of York, UK)

  • Edward Granter

    (Birmingham Business School, UK)

Abstract

While research on platform work has grown exponentially in recent years, the power dynamics between creators and algorithms on digital platforms, as well as their role in shaping online visibility, are yet to be fully understood. Against this backdrop, we ask: How does algorithmic power maintain its dominance and shape the nature of work for content creators? Through a systematic review of the literature on the relationship between algorithms and content creators, this article identified four core themes, namely: (i) market rationality underpinning visibility, (ii) potential power dislocation caused by folk theories, (iii) neo-normative control of creators through algorithms and (iv) subversion of beatific fantasies. Drawing from Tirapani and Willmott’s framework to theorise the power relations framing interactions between algorithms and creators, we argue that the fantasies fabricated by neoliberalism justify, endorse and ultimately support the dominance and dynamic power of algorithms over creators in content creative platforms.

Suggested Citation

  • Yin Liang & Jiaming Li & Jeremy Aroles & Edward Granter, 2025. "Content Creation within the Algorithmic Environment: A Systematic Review," Work, Employment & Society, British Sociological Association, vol. 39(4), pages 787-813, August.
  • Handle: RePEc:sae:woemps:v:39:y:2025:i:4:p:787-813
    DOI: 10.1177/09500170251325784
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    References listed on IDEAS

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    1. Ron Berman & Zsolt Katona, 2020. "Curation Algorithms and Filter Bubbles in Social Networks," Marketing Science, INFORMS, vol. 39(2), pages 296-316, March.
    2. Aurélie Leclercq-Vandelannoitte & Henri Isaac & Michel Kalika, 2014. "Mobile information systems and organisational control: beyond the panopticon metaphor?," European Journal of Information Systems, Taylor & Francis Journals, vol. 23(5), pages 543-557, September.
    3. Wallace Chipidza & Jie (Kevin) Yan, 2022. "The effectiveness of flagging content belonging to prominent individuals: The case of Donald Trump on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(11), pages 1641-1658, November.
    4. Dimitar Nikolov & Mounia Lalmas & Alessandro Flammini & Filippo Menczer, 2019. "Quantifying Biases in Online Information Exposure," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(3), pages 218-229, March.
    5. Harrigan, Paul & Daly, Timothy M. & Coussement, Kristof & Lee, Julie A. & Soutar, Geoffrey N. & Evers, Uwana, 2021. "Identifying influencers on social media," International Journal of Information Management, Elsevier, vol. 56(C).
    6. Niyati Aggrawal & Anuja Arora, 2019. "Behaviour of viewers: YouTube videos viewership analysis," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 20(1), pages 106-128.
    7. Ioannis Arapakis & Berkant Barla Cambazoglu & Mounia Lalmas, 2017. "On the feasibility of predicting popular news at cold start," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(5), pages 1149-1164, May.
    8. Nima Kordzadeh & Maryam Ghasemaghaei, 2022. "Algorithmic bias: review, synthesis, and future research directions," European Journal of Information Systems, Taylor & Francis Journals, vol. 31(3), pages 388-409, May.
    9. Keran Zhao & Yingda Lu & Yuheng Hu & Yili Hong, 2023. "Direct and Indirect Spillovers from Content Providers’ Switching: Evidence from Online Livestreaming," Information Systems Research, INFORMS, vol. 34(3), pages 847-866, September.
    10. repec:dau:papers:123456789/13420 is not listed on IDEAS
    11. Ro'ee Levy, 2021. "Social Media, News Consumption, and Polarization: Evidence from a Field Experiment," American Economic Review, American Economic Association, vol. 111(3), pages 831-870, March.
    12. Crosby, Paul & McKenzie, Jordi, 2021. "Should subscription-based content creators display their earnings on crowdfunding platforms? Evidence from Patreon," Journal of Business Venturing Insights, Elsevier, vol. 16(C).
    13. Hensmans, Manuel, 2021. "Exploring the dark and bright sides of Internet democracy: Ethos-reversing and ethos-renewing digital transformation," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    14. Manuel Hensmans, 2021. "Exploring the dark and bright sides of Internet democracy: Ethos-reversing and ethos-renewing digital transformation," ULB Institutional Repository 2013/321232, ULB -- Universite Libre de Bruxelles.
    15. Vivek K. Singh & Mary Chayko & Raj Inamdar & Diana Floegel, 2020. "Female librarians and male computer programmers? Gender bias in occupational images on digital media platforms," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(11), pages 1281-1294, November.
    16. Reisach, Ulrike, 2021. "The responsibility of social media in times of societal and political manipulation," European Journal of Operational Research, Elsevier, vol. 291(3), pages 906-917.
    17. Napoli, Philip M., 2015. "Social media and the public interest: Governance of news platforms in the realm of individual and algorithmic gatekeepers," Telecommunications Policy, Elsevier, vol. 39(9), pages 751-760.
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