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Understanding why certain individuals work well (or poorly) together as ateam is a key research focus in the psychological and behavioral sciences and afundamental problem for team-based organizations. Nevertheless, we have alimited ability to predict the social and work-related dynamics that willemerge from a given combination of team members. In this work, we model vocalturn-taking behavior within conversations as a parametric stochastic process ona network composed of the team members. More precisely, we model the dynamic ofexchanging the `speaker token' among team members as a random walk in a graphthat is driven by both individual level features and the conversation history.We fit our model to conversational turn-taking data extracted from audiorecordings of multinational student teams during undergraduate engineeringdesign internships. Through this real-world data we validate the explanatorypower of our model and we unveil statistically significant differences inspeaking behaviors between team members of different nationalities.

Conversational Turn-taking as a Stochastic Process on Networks