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

Fuente: arXiv

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Bibliographic Details
Main Authors:	Tsutsui, Hiroto, Hiraki, Takefumi, Hiroi, Yuichi, Hasegawa, Shoichi
Format:	Preprint
Published:	2025
Subjects:	Human-Computer Interaction Social and Information Networks
Online Access:	Acceder al recurso
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_version_	1866908563171966976
author	Tsutsui, Hiroto Hiraki, Takefumi Hiroi, Yuichi Hasegawa, Shoichi
author_facet	Tsutsui, Hiroto Hiraki, Takefumi Hiroi, Yuichi Hasegawa, Shoichi
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2509_23654
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	Community Analysis of Social Virtual Reality Based on Large-Scale Log Data of a Commercial Metaverse Platform Tsutsui, Hiroto Hiraki, Takefumi Hiroi, Yuichi Hasegawa, Shoichi Human-Computer Interaction Social and Information Networks 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.
title	Community Analysis of Social Virtual Reality Based on Large-Scale Log Data of a Commercial Metaverse Platform
topic	Human-Computer Interaction Social and Information Networks
url	https://arxiv.org/abs/2509.23654