My Favorite Streamer is an LLM: Discovering, Bonding, and Co-Creating in AI VTuber Fandom

2025-09-12

AI Summary

This study addresses two key gaps in AI VTuber fandom research: the opacity of human–AI interaction mechanisms and the unclear pathways of fan economy transformation. Employing a mixed qualitative approach—integrating netnography with community behavioral analysis—the study investigates how audiences cultivate sustained emotional bonds with algorithmically generated, non-human streamers through co-creation practices, affective event participation, and anthropomorphic projection. Findings reveal that (1) AI’s controllable unpredictability drives initial engagement; (2) collective affective practices reinforce communal belonging; (3) consistent persona design underpins long-term attachment; and (4) monetary support is reconfigured as participatory content co-production. Based on these insights, the study proposes the “active co-creative fandom” theoretical framework, elucidating a paradigm shift in fan economies—from unidirectional consumption to human–AI collaborative production—and offering critical implications for digital intimacy and platform governance in human–machine symbiosis.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Application Domains: Humanities & Computational Social Science
• Game Theory and Economic Paradigms: Cooperative Game Theory

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

AI VTubers, where the performer is not human but algorithmically generated, introduce a new context for fandom. While human VTubers have been substantially studied for their cultural appeal, parasocial dynamics, and community economies, little is known about how audiences engage with their AI counterparts. To address this gap, we present a qualitative study of Neuro-sama, the most prominent AI VTuber. Our findings show that engagement is anchored in active co-creation: audiences are drawn by the AI's unpredictable yet entertaining interactions, cement loyalty through collective emotional events that trigger anthropomorphic projection, and sustain attachment via the AI's consistent persona. Financial support emerges not as a reward for performance but as a participatory mechanism for shaping livestream content, establishing a resilient fan economy built on ongoing interaction. These dynamics reveal how AI Vtuber fandom reshapes fan-creator relationships and offer implications for designing transparent and sustainable AI-mediated communities.

Problem

• Studying audience engagement with AI VTubers
• Exploring co-creation dynamics in AI fandom
• Understanding financial support mechanisms in AI communities

Innovation

• Active co-creation with AI VTubers
• Anthropomorphic projection through emotional events
• Financial support as participatory content shaping