Community Analysis of Social Virtual Reality Based on Large-Scale Log Data of a Commercial Metaverse Platform

Hiroto Tsutsui, Takefumi Hiraki, Yuichi Hiroi, Shoichi Hasegawa

公開日: 2025/9/28

Abstract

This study quantitatively analyzes the structural characteristics of user communities within Social Virtual Reality (Social VR) platforms supporting head-mounted displays (HMDs), based on large-scale log data. By detecting and evaluating community structures from data on substantial interactions (defined as prolonged co-presence in the same virtual space), we found that Social VR platforms tend to host numerous, relatively small communities characterized by strong internal cohesion and limited inter-community connections. This finding contrasts with the large-scale, broadly connected community structures typically observed in conventional Social Networking Services (SNS). Furthermore, we identified a user segment capable of mediating between communities, despite these users not necessarily having numerous direct connections. We term this user segment `community hoppers' and discuss their characteristics. These findings contribute to a deeper understanding of the community structures that emerge within the unique communication environment of Social VR and the roles users play within them.

Community Analysis of Social Virtual Reality Based on Large-Scale Log Data of a Commercial Metaverse Platform | SummarXiv | SummarXiv