My Team Will Go On
| Autor: | Victor Chen, Mark E. Whiting, Vivian Yang, N'godjigui Junior Diarrassouba, Hancheng Cao, Lydia Stone, Michael S. Bernstein, Yu Jin Lee |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Computation and Language Knowledge management Median split Computer Networks and Communications Computer science business.industry education 05 social sciences Active engagement Human-Computer Interaction Decile Computer Science - Computers and Society Lasso regression Work (electrical) First person Organizational behavior Computers and Society (cs.CY) 0502 economics and business 0501 psychology and cognitive sciences business Computation and Language (cs.CL) 050203 business & management 050107 human factors Social Sciences (miscellaneous) |
| Zdroj: | Proceedings of the ACM on Human-Computer Interaction. 4:1-27 |
| ISSN: | 2573-0142 |
| DOI: | 10.1145/3432929 |
| Popis: | 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. Comment: CSCW 2020 Honorable Mention Award |
| Databáze: | OpenAIRE |
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