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.

'This is a timely book for team science, with a unique perspective that uses computational approaches to study the network effect on team performance. The book has a nice balance of theory, algorithms, and empirical studies. The authors possess years of experience in the field.'

Charu Aggarwal - IBM Research AI

'A comprehensive study that pushes forward our understanding of and ability to forecast and design team performance - a critical, yet complex human-subject phenomenon to which this book brings in-depth technical rigor.'

Leman Akoglu - Carnegie Mellon University

'This pioneering book is essential to technologists, data scientists, and researchers alike, offering a modern, computational approach to the science of teaming and how to manage the convergence of people, information, and technology in networked organizations.'

Norbou Buchler - US Army Data and Analysis Center

'Li and Tong have provided a thorough and insightful exploration of current research on teams in networks, linking computational techniques with results from the social sciences. A pleasure to read.'

Sucheta Soundarajan - Syracuse University

‘This brief volume is a valuable resource for managers, but managers with a strong background in data science, and for other technologists involved in designing systems that support user interactions … The added value of this book is provided by the mathematical formalisms used, which encode characteristics of the computational challenges discussed … The topical focus results in a unique volume that might lead interested readers to discover new research avenues … Recommended’

J. Brzezinski Source: Choice