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

2025-09-28

AI Summary

This study investigates the structural characteristics of user communities in social virtual reality (Social VR) platforms, addressing a gap in understanding how immersive environments shape community formation compared to traditional online social networks. Method: Leveraging large-scale head-mounted display (HMD) login logs from a commercial metaverse platform, we identify substantive interactions through prolonged co-presence behavior, construct user interaction networks, and apply community detection and network analysis techniques to characterize community topology. Contribution/Results: We find that Social VR communities exhibit a distinctive “small-scale, high internal cohesion, weak inter-community connectivity” structure—markedly divergent from conventional online networks. Crucially, we formally define and empirically identify a novel intermediary role: the “community jumper”—a user with sparse individual connections who nevertheless efficiently bridges multiple communities and facilitates cross-group information diffusion. This discovery reveals emergent community dynamics and user role paradigms unique to VR environments, providing empirical grounding and theoretical insight for metaverse community governance and immersive experience design.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Social Networks and Social Media: Analysis of web-mediated communications, communities, and crowds
• Web Mining and Content Analysis: Community question answering
• User Modeling, Personalization and Recommendation: Social recommender systems and personalization for the social Web

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.

Problem

• Analyzing structural characteristics of Social VR user communities
• Comparing community patterns between Social VR and traditional SNS
• Identifying community hoppers bridging isolated virtual reality groups

Innovation

• Analyzing communities via large-scale log data
• Detecting communities through substantial interaction metrics
• Identifying community hoppers as inter-community mediators