Evolution of networks in virtual reality: A scalable framework for studying social dynamics of small groups

Immersive technologies provide new possibilities to study social dynamics. In this paper, we develop a methodological framework for identifying and describing the evolution of group networks in virtual reality (VR). Leveraging longitudinal data on participants' interpersonal distances obtained in a collaborative virtual environment during a university course about VR we demonstrate how network methods can be applied and used to test propositions of social capital theory. Specifically, we use stochastic actor-oriented models (SAOMs) to explore the formation and change of social ties over time. Results showed that every additional connection to another group member reduced the likelihood of forming or maintaining a tie by less than half, whereas having a mutual connection (i.e., friend of friends) more than doubled the likelihood of tie formation or maintenance. This pattern supports our exploratory analysis that while students gradually became isolated in VR classrooms, their subgroups tended to persist. Also, participants were likely to change ties in ways that decreased imbalances in group identification and increased familiarity between dyad members, suggesting that social VR interactions are shaped by homophily. Overall, the substantive findings are indicative of bonding (ties inside the group), rather than bridging (ties outside the group), social capital. Methodologically, the integration of longitudinal network methods with VR tracking data opens new possibilities to learn about social dynamics.