"I'm not sure what difference is between their content and mine, other than the person itself": A Study of Fairness Perception of Content Moderation on YouTube
Renkai Ma, Yubo Kou
Abstract
How social media platforms could fairly conduct content moderation is gaining attention from society at large. Researchers from HCI and CSCW have investigated whether certain factors could affect how users perceive moderation decisions as fair or unfair. However, little attention has been paid to unpacking or elaborating on the formation processes of users' perceived (un)fairness from their moderation experiences, especially users who monetize their content. By interviewing 21 for-profit YouTubers (i.e., video content creators), we found three primary ways through which participants assess moderation fairness, including equality across their peers, consistency across moderation decisions and policies, and their voice in algorithmic visibility decision-making processes. Building upon the findings, we discuss how our participants' fairness perceptions demonstrate a multi-dimensional notion of moderation fairness and how YouTube implements an algorithmic assemblage to moderate YouTubers. We derive translatable design considerations for a fairer moderation system on platforms affording creator monetization.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 13ba2c94-60c5-45a4-9c8d-369bf9f24136Cited by top-tier papers10
- Decolonizing Content Moderation: Does Uniform Global Community Standard Resemble Utopian Equality or Western Power Hegemony?Farhana Shahid, Aditya VashisthaCHI 2023 · 63 citations
- Bystanders of Online Moderation: Examining the Effects of Witnessing Post-Removal ExplanationsShagun Jhaver, Himanshu Rathi, Koustuv SahaCHI 2024 · 19 citations
- The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social MediaAmaury Trujillo, Tiziano Fagni, Stefano CresciCSCW 2025 · 16 citations
- Chillbot: Content Moderation in the BackchannelJoseph Seering, Manas Khadka, Nava Haghighi, Tanya Yang et al.CSCW 2024 · 8 citations
- Governance of AI-Generated Content: A Case Study on Social Media PlatformsLan Gao, Abani Ahmed, Oscar Chen, Margaux Reyl et al.CHI 2026 · 3 citations
Related papers
- "Defaulting to boilerplate answers, they didn't engage in a genuine conversation": Dimensions of Transparency Design in Creator ModerationRenkai Ma, Yubo KouCSCW 2023 · 12 citations
- "Give Everybody [..] a Little Bit More Equity": Content Creator Perspectives and Responses to the Algorithmic Demonetization of Content Associated with Disadvantaged GroupsSara Kingsley, Proteeti Sinha, Clara Wang, Motahhare Eslami et al.CSCW 2022 · 38 citations
- "How advertiser-friendly is my video?": YouTuber's Socioeconomic Interactions with Algorithmic Content ModerationRenkai Ma, Yubo KouCSCW 2021 · 85 citations
- Why Creators Break Rules: Quantitative Evidence on Moral Disengagement and Self-ControlYao Li, Rie Helene (Lindy) Hernandez, Xinning Gui, Yubo KouCHI 2026 · 1 citation
- Creator-friendly Algorithms: Behaviors, Challenges, and Design Opportunities in Algorithmic PlatformsYoonseo Choi, Eun Jeong Kang, Min Kyung Lee, Juho KimCHI 2023 · 35 citations
