Detecting community structures in microblogs from behavioral interactions

Abstract

Microblogs have created a fast growing social network on the Internet and community detection is one of the subjects of great interest microblogs network analysis. The "follow" relationships highlighted in many existing methods are not sufficient to capture the actual relationship strength between users, which leads to imprecise communities of microblog users. In this paper, we presented the graph-based method for modeling microblog users and correspondingly proposed a new metric for obtaining the relationship quantitatively based on interaction activities. We then gave a hierarchical algorithm for community detection by incorporating the quantitative relationship strength and modularity density criterion. Experimental results showed and verified the effectiveness, applicability and efficiency of our method. © 2013 Springer-Verlag.