Community Structure of Complex Networks

Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks.
The thesis on which this book is based was honored with the 'Top 100 Excellent Doctoral Dissertations Award' from the Chinese Academy of Sciences and was nominated as the 'Outstanding Doctoral Dissertation' by the Chinese Computer Federation.

Hua-Wei Shen is currently an associate professor at the Institute of Computing Technology, Chinese Academy of Sciences, where he leads a research group on network analysis and social computing. His main research interests include network science, recommender system, and social network analysis. He received his PhD from the Graduate University of the Chinese Academy of Sciences in 2010. His doctoral thesis was honored with the 'Top 100 Excellent Doctoral Dissertations Award' by the Chinese Academy of Sciences and was nominated as the 'Outstanding Doctoral Dissertation' by the Chinese Computer Federation. He has published more than 40 papers in prestigious journals and top international conferences, including PLoS ONE, Physical Review E, Journal of Statistical Mechanics, WWW, CIKM, WSDM, and IJCAI.