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.
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"Defaulting to boilerplate answers, they didn't engage in a genuine conversation": Dimensions of Transparency Design in Creator Moderation
Transparency matters a lot to people who experience moderation on online platforms; much CSCW research has viewed offering explanations as one of the primary solutions to enhance moderation transparency. However, relatively little attention has been paid to unpacking what transparency entails in moderation design, especially for content creators. We interviewed 28 YouTubers to understand their moderation experiences and analyze the dimensions of moderation transparency. We identified four primary dimensions: participants desired the moderation system to present moderation decisions saliently, explain the decisions profoundly, afford communication with the users effectively, and offer repairment and learning opportunities. We discuss how these four dimensions are mutually constitutive and conditioned in the context of creator moderation, where the target of governance mechanisms extends beyond the content to creator careers. We then elaborate on how a dynamic, transparency perspective could value content creators' digital labor, how transparency design could support creators' learning, as well as implications for transparency design of other creator platforms.
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- Award ID(s):
- 2006854
- PAR ID:
- 10435872
- Date Published:
- Journal Name:
- Proceedings of the ACM on Human-Computer Interaction
- Volume:
- 7
- Issue:
- CSCW1
- ISSN:
- 2573-0142
- Page Range / eLocation ID:
- 1 to 26
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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