Twitch 上的仇恨突袭：理解直播社区中实时的人机协同攻击
Hate Raids on Twitch: Understanding Real-Time Human-Bot Coordinated Attacks in Live Streaming Communities
AI总结：
本研究通过分析 Twitch 子版块讨论，揭示仇恨突袭是人机协同利用直播系统攻击边缘化主播的群体攻击形式，并提出以可供性解释攻击机制、以设计即审核原则缓解滥用的建议。
摘要：
在线骚扰与内容审核在在线社区中已有充分记录。然而，新的情境与系统总会带来新的骚扰方式，并需要新的审核机制。本研究聚焦于仇恨突袭（hate raids），一种在直播社区中实时发生的群体攻击形式。通过对 Twitch 子版块（r/Twitch）中关于仇恨突袭讨论的定性分析，我们发现：（1）仇恨突袭作为一种人机协同的群体攻击，利用直播系统攻击边缘化主播及其他潜在群体，且可能在不违反规则的情况下实施；（2）边缘化主播遭受复合伤害，且平台支持不足；（3）审核策略绝大多数是技术性的，但主播在考虑自身边缘化状态与需求时，仍难以在审核与参与之间取得平衡。我们以可供性（affordances）为视角，解释仇恨突袭如何在直播系统中发生，并提出将“设计即审核”（moderation-by-design）作为一种视角，用于开发新功能或系统以减轻此类设计被滥用的潜在风险。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
