Computational Approaches to the Network Science of Teams

How do communication patterns, team composition, and the networks around a group relate to its performance? In Computational Approaches to the Network Science of Teams, Liangyue Li and Hanghang Tong bring computational thinking to these questions, treating teamwork as a networked process that can be studied, forecast, and potentially improved.

This research-oriented review connects social-network structure with models and algorithms for understanding team performance. It offers a useful framework for readers interested in the analytical side of collaboration: not just who is on a team, but how people, tasks, and relationships combine.

From team patterns to performance predictions

The book first considers how team performance can be characterized, with examples spanning collective intelligence, online games, sports, and GitHub. It then turns to prediction, including long-term performance forecasting, performance trajectories, and part–whole outcome prediction. These topics show how network data can be brought to bear on different stages and scales of team work.

Designing and explaining better team systems

Later chapters examine optimization problems such as team formation and member replacement, then consider how network-based predictions and optimization can be explained. The focus is both computational and interpretive: methods are presented in the context of questions about what can be changed, what can be anticipated, and how analytical results might be understood.

Where human–agent teams fit

A chapter on human–agent teaming extends the discussion to collaboration involving people and computational agents. The book closes with conclusions and future research directions, making its scope relevant to readers tracking an emerging area as well as those seeking a structured review of its methods and open challenges.

For readers working with networks and teams

Researchers and practitioners in data mining, social-network analysis, and computational studies of organizations will find a focused account of models and applications for team characterization, prediction, optimization, and explanation. Advanced students exploring these fields may also value the chapter-by-chapter map of key problems and research directions.

For a deeper look at teamwork through the structure of the networks that connect people and tasks, this ebook brings the central questions and computational approaches together in one volume.