Text to Teamwork

Abstract: Modern challenges such as emergency response, software development, and deep space exploration necessitate the collaboration of interdependent teams in multiteam systems (MTSs). We propose a novel approach to identify key communicative performance drivers in MTSs. Existing research primarily focuses on macro-level dynamics, overlooking micro-level communication patterns. To address this gap, we utilize dialog act labels to study communication in MTSs. We analyze data from Project RED Design, a cooperative MTS decision-making activity, and employ natural language processing techniques to identify dialog act transitions and measure their impact on mission performance. Our study enhances communication strategies for spaceflight MTSs and can be adapted for other MTSs, aiding in protocol development and training programs. This approach enables timely interventions and improved success in future space exploration missions.

Related work:

Chan, M. Contractor, N., Begerowski, S., Bell, S., Cao, H., Kush, J., Mathieu, J. (2024, Apr 17-20). Text to Teamwork: Decoding Team Dynamics with Computer-Aided Text Analysis [Alternative Session Type]. Society for Industrial and Organizational Psychology Annual Conference, Chicago, IL, United States.

Shah, M.,Chan, M., Youn, H., DeChurch, L., Contractor, N. (2023, Oct. 6 – 8). Uncovering Effective Sequences of Dialog Acts in High-Performance Multiteam Systems. [Poster Presentation]. Organizational Communication Mini Conference, New Brunswick, NJ, United States.

Markov transition matrix of dialogue act transitions showing that high-performing teams tended to follow questions with statements, whereas low-performing teams tended to follow questions with more questions

Research supported by NASA awards NNX15AM32G, 80NSSC18K0221, and 80NSSC18K0276

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