The I in Team

The I in Team: Mining Personal Social Interaction Routine with Topic Models from Long-Term Team Data

Zhang, Y. (TU Delft Pattern Recognition and Bioinformatics)
Olenick, Jeffrey (Michigan State University)
Chang, Chu-Hsiang (Michigan State University)
Kozlowski, Steve W.J. (Michigan State University)
Hung, H.S. (TU Delft Pattern Recognition and Bioinformatics)

2018

Social interaction plays a key role in assessing teamwork and collaboration. It becomes particularly critical in team performance when coupled with isolated, confined, and extreme conditions such as undersea missions. This work investigates how social interactions of individual members in a small team evolve during the course of a long duration mission. We propose to use a topic model to mine individual social interaction patterns and examine how the dynamics of these patterns have an effect on self-assessment of mood and team cohesion. Specifically, we analyzed data from a 6-person crew wearing Sociometric badges over a 4-month mission. Our results show that our method can extract the latent structure of social contexts without supervision. We demonstrate how the extracted patterns based on probabilistic models can provide insights on common behaviors at various temporal resolutions and exhibit links with self-report affective states and team cohesion.

Machine learning
Team dynamics
Wearable

http://resolver.tudelft.nl/uuid:893a1db8-0dbc-44e6-995c-b043bfec882d

https://doi.org/10.1145/3172944.3172997

Association for Computing Machinery (ACM), New York, NY

2022-04-08

978-1-4503-4945-1

IUI 2018 - Proceedings of the 23rd International Conference on Intelligent User Interfaces

IUI 2018, 2018-03-07 → 2018-03-11, Tokyo, Japan

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2018 Y. Zhang, Jeffrey Olenick, Chu-Hsiang Chang, Steve W.J. Kozlowski, H.S. Hung