Personal network features are embodied in real-time social interaction dynamics

People navigate dozens of social interactions daily. Through these, they construct and maintain diverse social networks. While personal dispositions drive how people interact and connect others, the resulting networks feed back into daily social experiences by creating interaction opportunities and modulating cognitive processes. Here, we show that people's moment-to-moment interaction behaviors are informative of the structure of their personal social network, even if the interaction occurs between strangers. We paired 104 strangers to perform an interactive motor task and investigated whether emergent leader-follower roles and spontaneous movement synchronization reflected similarities or differences in their personal networks. Participants with tighter networks (smaller, denser, more constrained, and with fewer communities) relative to the interaction partner adapted their movements to the partner more. Using multivariate temporal response functions (mTRF) to measure neural encoding of self and other's movements, we found that, conversely, participants with less tight networks exhibited higher neural encoding of their partner's movements. This suggests that the network effect on behavioral adaptation was unlikely to be driven by heightened monitoring of the partner. Higher spontaneous movement synchronization was associated with higher personality agreeableness and personality similarity between interacting partners. Our results demonstrate that signatures of personal social environment manifest dynamically in real-time behaviors and that these effects are independent of personality effects. Thus, social networks set an additional context for interpersonal interaction even for partners without a prior relationship.