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(Mis)align: a simple dynamic framework for modeling interpersonal coordination.
Grace Qiyuan Miao1, Rick Dale2, Alexia Galati3
1Department of Communication, University of California, Los Angeles, CA, USA. q.miao@ucla.edu.
This study introduces a computational framework to model interpersonal behavioral coordination, including synchrony and complementarity. Task constraints significantly predict agent behaviors and replicate human interaction patterns.
Area of Science:
- Computational Social Science
- Behavioral Dynamics
- Human-Computer Interaction
Background:
- Human interactions involve complex coordination patterns like synchrony and complementarity.
- Understanding these dynamics is crucial for effective communication and collaboration.
Purpose of the Study:
- To develop a computational framework for analyzing interpersonal behavioral synchrony and complementarity.
- To investigate the influence of task context on these coordination dynamics.
- To validate the framework against human interaction data.
Main Methods:
- Development of a computational model incorporating task constraints (active, inactive, inhibitory).
- Simulation of agent behaviors under varying task conditions.
- Analysis of simulated data to identify patterns of synchrony and complementarity.
- Comparison of simulation results with empirical human interaction data.
Main Results:
- Task constraints were found to be robust predictors of simulated agent behaviors over time.
- The framework successfully reproduced general patterns observed in human interaction data.
- The study highlights the significant role of task context in mediating behavioral coordination.
Conclusions:
- The developed framework offers a novel approach to understanding interpersonal dynamics in communication.
- Task-dependent constraints are key determinants of behavioral synchrony and complementarity.
- Results support broader theories of synergistic self-organization in communication systems.

