In the summer of 2021, users on the livestreaming platform Twitch experienced a wave of "hate raids," a form of attack that overwhelms a target's chatroom with hateful messages, often with the aid of bots and automation. Utilizing a mixed-methods approach, we combine interviews with streamers and third-party bot developers with a quantitative measurement of this phenomenon across the platform. We present evidence that confirms that hate raids are highly-targeted, hate-driven attacks, but we also observe another mode of hate raid with similarities to networked harassment and subcultural trolling. We show that the streamers who self-identified as LGBTQ+ and/or Black were disproportionately targeted, and that the content of these hate raid messages were most commonly rooted in anti-Black racism and antisemitism. We also document how the threat of these attacks elicited both proactive and rapid, reactive community responses. These results have implications for future design of livestreaming platforms to better prepare for the experiences of at-risk communities in a way that is cognizant of a division of labor between community moderators, tool-builders, and platforms.

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https://hci.top/en/papers/cscw/124506/2023

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2023
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