/UnmuteAll: Modeling Verbal Communication Patterns of Collaborative Contexts in MOBA Games

Abstract

Team communication plays a vital role in supporting collaboration in multiplayer online games. Therefore, numerous studies were conducted to examine communication patterns in esports teams. While non-verbal communication has been extensively investigated, research on assessing voice-based verbal communication patterns remains relatively understudied. In this study, we propose a framework that automatically assesses verbal communication patterns by constructing networks with utterances transcribed from voice recordings. Through a data collection study, we obtained 84 game sessions from five League of Legends teams and subsequently investigated how verbal communication patterns varied across different conditions. As a result, we revealed that esports players exhibited broader and more balanced participation in collaborative situations, increased utterances over time with the largest rise in decision making, and team-level differences that were contingent on effective professional training. Building upon these findings, this study provides a generalizable tool for analyzing effective team communication.