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Online harassment and content moderation have been well-documented in online communities. However, new contexts and systems always bring new ways of harassment and need new moderation mechanisms. This study focuses on hate raids, a form of group attack in real-time in live streaming communities. Through a qualitative analysis of hate raids discussion in the Twitch subreddit (r/Twitch), we found that (1) hate raids as a human-bot coordinated group attack leverages the live stream system to attack marginalized streamers and other potential groups with(out) breaking the rules, (2) marginalized streamers suffer compound harms with insufficient support from the platform, (3) moderation strategies are overwhelmingly technical, but streamers still struggle to balance moderation and participation considering their marginalization status and needs. We use affordances as a lens to explain how hate raids happens in live streaming systems and propose moderation-by-design as a lens when developing new features or systems to mitigate the potential abuse of such designs.
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Towards a Design Framework for Data-Driven Game Streaming: A Multi-Stakeholder Approach
Research on live streaming systems that incorporate real-time data, such as game or viewer data, have been a topic of HCI research for some time. Despite the potential of data-driven game streaming interfaces, translating this research into practice faces two key challenges. First, the design space afforded by data-driven game streaming systems is not yet well understood, making it difficult to identify how designs might meet users' existing and potential needs. Second, adoption of these systems relies on engagement with the entire streaming ecosystem, which includes developers, streamers, moderators, and viewers, rather than with just one group. Through a two-phase design study, we investigate the expectations, desires, and experiences of streaming stakeholders, shedding light on how data-driven game streaming systems can meet their needs. Building upon these insights and drawing upon previous research, we propose a design framework aimed at analyzing and generating data-driven game streaming designs, thereby moving toward formalizing the design and development of such systems.
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- Award ID(s):
- 1942087
- PAR ID:
- 10633174
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- Proceedings of the ACM on Human-Computer Interaction
- Volume:
- 8
- Issue:
- CHI PLAY
- ISSN:
- 2573-0142
- Page Range / eLocation ID:
- 1 to 28
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3677107
