Discovering content-based behavioral roles in social networks

Role analysis helps us characterize users' interactions in a social network. However, previously proposed methods are mainly based on structural analysis of social networks rather than content-based behavior analysis. Therefore, we propose a method to use the content-based behavioral features extracted from user-generated content and behavior patterns to identify users' roles and to explore role change patterns in social networks. The proposed method allows a user to play multiple roles in a social network and can identify roles without using any pre-defined roles. Thus, it provides a more general and flexible way to perform role analyses in social networks. The experimental results show that the proposed method can find various roles in different social networks, additional roles that haven't been previously aware of, and some interesting role change patterns. The results may help us better understand the characteristics and trends of a social network, and formulate more effective management strategies. (C) 2013 Elsevier B.V. All rights reserved.