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You Can (Not) Say What You Want: Using Algospeak to Contest and Evade Algorithmic Content Moderation on TikTok

Steen, Ella, Yurechko, Kathryn, Klug, Daniel·2023·Social Media + Society
DOI 10.1177/20563051231194586
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Abstract

Social media users have long been aware of opaque content moderation systems and how they shape platform environments. On TikTok, creators increasingly utilize algospeak to circumvent unjust content restriction, meaning, they change or invent words to prevent TikTok’s content moderation algorithm from banning their video (e.g., “le$bean” for “lesbian”). We interviewed 19 TikTok creators about their motivations and practices of using algospeak in relation to their experience with TikTok’s content moderation. Participants largely anticipated how TikTok’s algorithm would read their videos, and used algospeak to evade unjustified content moderation while simultaneously ensuring target audiences can still find their videos. We identify non-contextuality, randomness, inaccuracy, and bias against marginalized communities as major issues regarding freedom of expression, equality of subjects, and support for communities of interest. Using algospeak, we argue for a need to improve contextually informed content moderation to valorize marginalized and tabooed audiovisual content on social media.

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  • The rationale for content moderation decisions is poorly communicated, and LGBTQ+ users have to rely on their own knowledge.

    “Overall, in a context in which the rationale for content moderation decisions is poorly communicated (Steen, Yurechko, and Klug 2023), LGBTQ+ users have to rely on their own knowledge.”

    From Staring Back at the Surveillance Gaze: The Resistance of LGBTQ+ Users on Social Media (2026) · cites this paper as Steen, Yurechko, and Klug 2023

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Metadata

Authors
Steen, E., Yurechko, K., & Klug, D.
Affiliations
  • Gordon College, USA
  • Washington and Lee University, USA
  • Carnegie Mellon University, USA
ORCID
Klug, Daniel
Venue
Social Media + Society
Publisher
SAGE Publications
Published
2023-07
Volume
9
Issue
3
ISSN
2056-3051
DOI
10.1177/20563051231194586
Cited by
111
References
2
Language
en
Licence
creativecommons.org/licenses/by-nc/4.0/ (unspecified)

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