Virtual Stars, Real Fans: Understanding the VTuber Ecosystem
Yiluo Wei, Gareth Tyson
TL;DR
This paper tackles understanding VTuber viewers by performing a large-scale, data-driven study on Bilibili to characterize core viewers and predict future paying members. It builds a rich dataset of 2.7 million live sessions and 3.6 billion chat messages across thousands of VTubers, analyzes behavioral and linguistic patterns, and introduces FanRanker, a model that ranks viewers by their likelihood of becoming members. Key findings show that potential members exhibit higher pre-purchase engagement and closer alignment with VTuber chat culture, but post-purchase engagement wanes and renewal is limited, with a strong need for retention strategies and moderation given rising toxicity. FanRanker demonstrates practical utility by identifying a small subset of viewers (top 50) who are most likely to convert to paying members, offering tangible guidance for VTubers to grow and monetize their fan communities, with plans to extend analysis to other platforms.
Abstract
Livestreaming by VTubers -- animated 2D/3D avatars controlled by real individuals -- have recently garnered substantial global followings and achieved significant monetary success. Despite prior research highlighting the importance of realism in audience engagement, VTubers deliberately conceal their identities, cultivating dedicated fan communities through virtual personas. While previous studies underscore that building a core fan community is essential to a streamer's success, we lack an understanding of the characteristics of viewers of this new type of streamer. Gaining a deeper insight into these viewers is critical for VTubers to enhance audience engagement, foster a more robust fan base, and attract a larger viewership. To address this gap, we conduct a comprehensive analysis of VTuber viewers on Bilibili, a leading livestreaming platform where nearly all VTubers in China stream. By compiling a first-of-its-kind dataset covering 2.7M livestreaming sessions, we investigate the characteristics, engagement patterns, and influence of VTuber viewers. Our research yields several valuable insights, which we then leverage to develop a tool to "recommend" future subscribers to VTubers. By reversing the typical approach of recommending streams to viewers, this tool assists VTubers in pinpointing potential future fans to pay more attention to, and thereby effectively growing their fan community.