DISSECT: Data-Intensive Socially Similar Evolving Community Tracker

Abstract

This chapter examines the problem of tracking community in social networks inferred from online interactions by tracking evolution of known subgroups over time. Finding subgroups within social networks is important for understanding and possibly influencing the formation and evolution of online com- munities. A variety of approaches have been suggested to address this problem and the corresponding research literature on centrality, clustering, and optimization methods for finding subgroupings is reviewed. This review will include a critical analysis of the limitations of past approaches. The focus of the chapter will then turn to novel methods for tracking online community interaction. First, the method proposed by Chin and Chignell called SCAN will be briefly introduced, where a combination of heuristic methods is used to identify subgroups in a manner that can potentially scale up to very large social networks. Then, we present the DISSECT method where multiple known subgroups within a social network are tracked in terms of similarity-based cohesiveness over time. The DISSECT method relies on cluster analysis of snapshots of network activity at different points in time followed by similarity analysis of subgroup evolution over successive time periods. The DISSECT method can be supplemented with behavioral measures of sense of com- munitywhere administration of a questionnaire is feasible. Finally, we conclude the chapterwith a discussion on possible applications and use of the DISSECT method. A. Chin Nokia Research Center, Building 2, No. 5 Donghuan Zhonglu, Economic and Technological Development Area, Beijing 100176, China e-mail: alvin.chinnokia.com M. Chignell Department of Mechanical and Industrial Engineering, University of Toronto, 5 Kings College Road, Toronto, Ontario,M5S 3G8, Canada e-mail: chignellmie.utoronto.ca A. Abraham et al. (eds.), Computational Social Network Analysis, Computer Communications and Networks, DOI 10.1007/978-1-84882-229-0 4, c Springer-Verlag London Limited 2010 81