Time-Dynamic Semantic-Activity Entanglement: Quantifying Communication-Based Synchrony in Collaborative VR
Pooja Pol, Jianing Zhang, Qing Huang
Collaborative virtual reality (VR) produces rich multimodal traces of team behavior, yet practical methods for characterizing time-varying team communication remain limited. We present time-dynamic semantic-activity entanglement (TSAE), inspired by the entanglement concept introduced by Gloor et al. (2022), to describe communication-based team synchronization within discrete time windows. TSAE is modeled by combining relative speaking activity with contextual semantic alignment for participant pairs, which is aggregated into participant-level trajectories and summarized through the Gini coefficient to understand the distribution of team-level communication synchrony. This approach is employed with German-language transcripts from fifteen collaborative VR gameplay sessions. Transcript utterances are represented using a long-context embedding model with a late-chunking strategy and analyzed within fixed game-time windows. A representative session illustrates shifting dyadic alignment and low-to-moderate participant contributions, with sporadic periods of high entanglement. Across fifteen game sessions, the metrics indicate complementary insights, offering a qualitative contrast to the core-periphery pattern reported in the foundational work. Hence, these descriptive findings support the study of communication as a dynamic process and provide a mathematically grounded approach to analyze its evolving distribution in shared interactive VR spaces.
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