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My Team Will Go On: Differentiating High and Low Viability Teams through Team Interaction

Authors:

N'godjigui Junior Diarrassouba,

Mark E. Whiting,

Michael S. BernsteinAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 4, Issue CSCW3

Article No.: 230, Pages 1 - 27

https://doi.org/10.1145/3432929

Published: 05 January 2021 Publication History

Abstract

Understanding team viability --- a team's capacity for sustained and future success --- is essential for building effective teams. In this study, we aggregate features drawn from the organizational behavior literature to train a viability classification model over a dataset of 669 10-minute text conversations of online teams. We train classifiers to identify teams at the top decile (most viable teams), 50th percentile (above a median split), and bottom decile (least viable teams), then characterize the attributes of teams at each of these viability levels. We find that a lasso regression model achieves an accuracy of .74--.92 AUC ROC under different thresholds of classifying viability scores. From these models, we identify the use of exclusive language such as 'but' and 'except', and the use of second person pronouns, as the most predictive features for detecting the most viable teams, suggesting that active engagement with others' ideas is a crucial signal of a viable team. Only a small fraction of the 10-minute discussion, as little as 70 seconds, is required for predicting the viability of team interaction. This work suggests opportunities for teams to assess, track, and visualize their own viability in real time as they collaborate.

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Index Terms

My Team Will Go On: Differentiating High and Low Viability Teams through Team Interaction
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 4, Issue CSCW3

CSCW

December 2020

1825 pages

EISSN:2573-0142

DOI:10.1145/3446568

Editor:
Jeff Nichols
Apple Inc., United States

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Published: 05 January 2021

Published in PACMHCI Volume 4, Issue CSCW3

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Vaithilingam PArawjo IGlassman E(2024)Imagining a Future of Designing with AI: Dynamic Grounding, Constructive Negotiation, and Sustainable MotivationProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661525(289-300)Online publication date: 1-Jul-2024
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