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1. Coordination and Collaboration: How do Volunteer Moderators Work as a Team in Live Streaming Communities?

   https://doi.org/10.1145/3491102.3517628  

   Cai, Jie; Wohn, Donghee Yvette (April 2022, CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems)

   Volunteer moderators (mods) play significant roles in developing moderation standards and dealing with harmful content in their micro-communities. However, little work explores how volunteer mods work as a team. In line with prior work about understanding volunteer moderation, we interview 40 volunteer mods on Twitch — a leading live streaming platform. We identify how mods collaborate on tasks (off-streaming coordination and preparation, in-stream real-time collaboration, and relationship building both off-stream and in-stream to reinforce collaboration) and how mods contribute to moderation standards (collaboratively working on the community rulebook and individually shaping community norms). We uncover how volunteer mods work as an effective team. We also discuss how the affordances of multi-modal communication and informality of volunteer moderation contribute to task collaboration, standards development, and mod’s roles and responsibilities. 

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2. Volunteer Moderators in Twitch Micro Communities: How They Get Involved, the Roles They Play, and the Emotional Labor They Experience

   https://doi.org/10.1145/3290605.3300390  

   Wohn, Donghee Yvette (May 2019, Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems)

   The ability to engage in real-time text conversations is an important feature on live streaming platforms. The moderation of this text content relies heavily on the work of unpaid volunteers. This study reports on interviews with 20 people who moderate for Twitch micro communities, defined as channels that are built around a single or group of streamers, rather than the broadcast of an event. The study identifies how people become moderators, their different styles of moderating, and the difficulties that come with the job. In addition to the hardships of dealing with negative content, moderators also have complex interpersonal relationships with the streamers and viewers, where the boundaries between emotional labor, physical labor, and fun are intertwined. 

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3. Hate Raids on Twitch: Understanding Real-Time Human-Bot Coordinated Attacks in Live Streaming Communities

   https://doi.org/10.1145/3610191  

   Cai, Jie; Chowdhury, Sagnik; Zhou, Hongyang; Wohn, Donghee Yvette (September 2023, Proceedings of the ACM on Human-Computer Interaction)

   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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4. (In)visible moderation: A digital ethnography of marginalized users and content moderation on Twitch and Reddit

   https://doi.org/10.1177/14614448221109804  

   Thach, Hibby; Mayworm, Samuel; Delmonaco, Daniel; Haimson, Oliver (July 2022, New Media & Society)

   Research suggests that marginalized social media users face disproportionate content moderation and removal. However, when content is removed or accounts suspended, the processes governing content moderation are largely invisible, making assessing content moderation bias difficult. To study this bias, we conducted a digital ethnography of marginalized users on Reddit’s /r/FTM subreddit and Twitch’s “Just Chatting” and “Pools, Hot Tubs, and Beaches” categories, observing content moderation visibility in real time. We found that on Reddit, a text-based platform, platform tools make content moderation practices invisible to users, but moderators make their practices visible through communication with users. Yet on Twitch, a live chat and streaming platform, content moderation practices are visible in channel live chats, “unban appeal” streams, and “back from my ban” streams. Our ethnography shows how content moderation visibility differs in important ways between social media platforms, harming those who must see offensive content, and at other times, allowing for increased platform accountability. 

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5. Categorizing Live Streaming Moderation Tools: An Analysis of Twitch

   https://doi.org/10.4018/IJICST.2019070103  

   Cai, Jie; Wohn, Donghee Yvette (July 2019, International Journal of Interactive Communication Systems and Technologies)

   Twitch is one of the largest live streaming platforms and is unique from other social media in that it supports synchronous interaction and enables users to engage in moderation of the content through varied technical tools, which include auto-moderation tools provided by Twitch, third-party applications, and home-brew apps. The authors interviewed 21 moderators on Twitch and categorized the current features of real-time moderation tools they are using into four functions (chat control, content control, viewer control, settings control) and explored some new features of tools that they wish to own (e.g., grouping chat by languages, pop out window to hold messages, chat slow down, a set of buttons with pre-written/pre-message content, viewer activity tracking, all in one). Design implications provide suggestions for chatbots and algorithm design and development. 

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