Computational approaches to the network science of teams
Liangyue Li, Hanghang Tong
"Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: What communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends"--
Year of publication: |
2021
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---|---|
Authors: | Li, Liangyue ; Tong, Hanghang |
Publisher: |
2021: Cambridge : Cambridge University Press |
Subject: | Arbeitsgruppe | Team | Unternehmensnetzwerk | Business network | Data Mining | Data mining | Performance-Messung | Performance measurement |
Description of contents: |
Team performance characterization -- Team performance prediction -- Team performance optimization -- Team performance explanation -- Human agent teaming -- Conclusion and future work.
Table of Contents [gbv.de]
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