/UnmuteAll: Modeling Verbal Communication Patterns of Collaborative Contexts in MOBA Games
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917165919109120 |
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| author | Son, Yongchan Jang, Jahun An, Been Kang, Jimoon Park, Eunji |
| author_facet | Son, Yongchan Jang, Jahun An, Been Kang, Jimoon Park, Eunji |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_20116 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | /UnmuteAll: Modeling Verbal Communication Patterns of Collaborative Contexts in MOBA Games Son, Yongchan Jang, Jahun An, Been Kang, Jimoon Park, Eunji Human-Computer Interaction 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. |
| title | /UnmuteAll: Modeling Verbal Communication Patterns of Collaborative Contexts in MOBA Games |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2512.20116 |