Livestream communities for AI-generated video content: Viewers’ motivations and perceptions of toxicity and moderation

AI is transforming live streaming with new communities forming around channels featuring automated or prompt-based AI-generated videos. By introducing AI as an active and sometimes unpredictable participant in community interactions, traditional creator-audience and audience-audience relations are disrupted, presenting challenges for toxicity and moderation. This paper presents findings from a mixed-methods survey of viewers ( ) to understand their motivations for engaging with AI content, perceptions of toxicity, and moderation preferences. Our findings highlight the variety of viewer motivations of the participants of the surveyed communities with both individual and social aspects, that viewers were more engaged by AI interactions and user-generated prompts than by other viewers, and that toxicity arose from various sources and negatively related to the sense of community, with most viewers favouring in-community moderation. Our insights represent an initial descriptive examination of communities that rely exclusively on fast-paced AI-generated content and underscore the need for updated moderation strategies to sustain healthier dynamics in AI livestreams • We study new livestream communities around AI-generated videos • We identify individual and social motivations of viewers • We identify sources of toxicity in the communities • We explore how the community members react to toxicity and think about moderation

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Publication Details

Journal
International Journal of Human-Computer Studies
Published
2026-03-04
DOI
https://doi.org/10.1016/j.ijhcs.2026.103780
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Livestream communities for AI-generated video content: Viewers’ motivations and perceptions of toxicity and moderation

Dennis Nguyen, Julian Frommel, Alkim Almila Akdag, Karin van Es et al.
International Journal of Human-Computer Studies
Hate Speech and Cyberbullying Detection
article

Livestream communities for AI-generated video content: Viewers’ motivations and perceptions of toxicity and moderation

Dennis Nguyen, Julian Frommel, Alkim Almila Akdag, Karin van Es, Sacha Gutierrez
article en

Abstract

AI is transforming live streaming with new communities forming around channels featuring automated or prompt-based AI-generated videos. By introducing AI as an active and sometimes unpredictable participant in community interactions, traditional creator-audience and audience-audience relations are disrupted, presenting challenges for toxicity and moderation. This paper presents findings from a mixed-methods survey of viewers ( ) to understand their motivations for engaging with AI content, perceptions of toxicity, and moderation preferences. Our findings highlight the variety of viewer motivations of the participants of the surveyed communities with both individual and social aspects, that viewers were more engaged by AI interactions and user-generated prompts than by other viewers, and that toxicity arose from various sources and negatively related to the sense of community, with most viewers favouring in-community moderation. Our insights represent an initial descriptive examination of communities that rely exclusively on fast-paced AI-generated content and underscore the need for updated moderation strategies to sustain healthier dynamics in AI livestreams • We study new livestream communities around AI-generated videos • We identify individual and social motivations of viewers • We identify sources of toxicity in the communities • We explore how the community members react to toxicity and think about moderation

International Journal of Human-Computer StudiesVol. 211
Utrecht University (NL)
Openalex Percentile: Top 38%
Hate Speech and Cyberbullying Detection
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