Understanding Multi-platform Social VR Consumer Opinions: A Case Study in VRChat Using Topics Modeling of Reviews

Due to the significant advancements in virtual reality (VR) technologies over the years, more research has been done on how these technologies could promote more effective communication in social applications to enhance collaboration and social connectivity. Most studies about social VR conducted experimental tasks in different communication contexts to evaluate communication quality, which has limited relevance to the VR industries and ambiguous generalizability of findings outside of lab settings. This study tries to solve this problem by conducting a case study on one of the most popular commercial social VR applications to understand what factors impact consumers’ user experience in social VR applications. We used the Structural Topic Model (STM) based text mining of VRChat’s steam reviews to explore topics that users discuss and classified the topics into four clusters, including avatars and behaviors, complaints, hardware and connection, and recommendation. The implications for game developers and future social VR research are discussed.