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The Scientific World Journal
Volume 2014, Article ID 105428, 11 pages
http://dx.doi.org/10.1155/2014/105428
Research Article

Content Patterns in Topic-Based Overlapping Communities

Industrial Engineering Department, University of Chile, Av. República 701, 8370439 Santiago, Chile

Received 13 January 2014; Accepted 19 February 2014; Published 9 April 2014

Academic Editors: H. R. Karimi, X. Yang, and Z. Yu

Copyright © 2014 Sebastián A. Ríos and Ricardo Muñoz. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Understanding the underlying community structure is an important challenge in social network analysis. Most state-of-the-art algorithms only consider structural properties to detect disjoint subcommunities and do not include the fact that people can belong to more than one community and also ignore the information contained in posts that users have made. To tackle this problem, we developed a novel methodology to detect overlapping subcommunities in online social networks and a method to analyze the content patterns for each subcommunities using topic models. This paper presents our main contribution, a hybrid algorithm which combines two different overlapping sub-community detection approaches: the first one considers the graph structure of the network (topology-based subcommunities detection approach) and the second one takes the textual information of the network nodes into consideration (topic-based subcommunities detection approach). Additionally we provide a method to analyze and compare the content generated. Tests on real-world virtual communities show that our algorithm outperforms other methods.