Paper

Conversational Turn-taking as a Stochastic Process on Networks

O'Bryan, Lisa, Salas, Eduardo, Beier, Margaret E, Wettergreen, Matthew, Zajac, Stephanie, Paoletti, Jensine, Segarra, Santiago, Sabharwal, Ashutosh

2023

Overview

Understanding why certain individuals work well (or poorly) together as a team is a key research focus in the psychological and behavioral sciences and a fundamental problem for team-based organizations. Nevertheless, we have a limited ability to predict the social and work-related dynamics that will emerge from a given combination of team members. In this work, we model vocal turn-taking behavior within conversations as a parametric stochastic process on a network composed of the team members. More precisely, we model the dynamic of exchanging the `speaker token' among team members as a random walk in a graph that is driven by both individual level features and the conversation history. We fit our model to conversational turn-taking data extracted from audio recordings of multinational student teams during undergraduate engineering design internships. Through this real-world data we validate the explanatory power of our model and we unveil statistically significant differences in speaking behaviors between team members of different nationalities.

• Publisher: Cornell University Library, arXiv.org
• Subject: Audio data / Design engineering / Engineering education / Random walk / Stochastic models / Stochastic processes