Social VR is emerging with commercialized VR equipment in recent years. In 2020, the COVID-19 global pandemic dramatically changed people’s life. Governments recommend people stay at home, and the number of people in social VR also increased. This study focused on VRChat, one of the most popular and free to play social VR games. A systematic observation and behavior mapping had been conducted for a week (five weekdays and two weekends) in three maps (Worlds). Based on the VRChat user number and time relationship, each map’s observation was conducted every 2 hours, starting from 8:00 to 22:00 (JST), and over 1000 users have been observed. And the map selection is based on language use and cultural elements in the map, including Japan, China, and English-speaking countries. People’s positions on the map, behaviors, topics of conversation, and language use have been collected. The mapping results will present on maps, and other data such as the number of people, people’s behaviors, and distance between people will be statistically analyzed by Excel and SPSS (Statistical Product and Service Solutions). This study will discuss and explore the following research objectives: 1. Find out spatial elements in the virtual environment and what attracts people. 2. Categorize people’s social behaviors in virtual environments. 3. Analyze people’s distance when they are socializing. The results will reveal people’s spatial preference in social VR games and identified critical issues for future design and research in social VR.
Maozhu Mao, Chiba University, Japan
Stream: Linguistics, Language & Psychology/Behavioral Science
This paper is part of the ACP2021 Conference Proceedings (View)
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