Abstract. The efficient identification of communities with common interests is a key consideration in applying targeted advertising and viral marketing to online social networking sites. Existing methods involve large scale community detection on the entire social network before determining the interests of individuals within these communities. This approach is both computationally intensive and may result in communities without a common interest. We propose an efficient topologicalbased approach for detecting communities that share common interests on Twitter. Our approach involves first identifying celebrities that are representative of an interest category before detecting communities based on linkages among followers of these celebrities. We also study the network characteristics and tweeting behaviour of these communities, and the effects of deepening or specialization of interest on their community structures. In particular, our evaluation on Twitter shows that these detected communities comprise members who are well-connected, cohesive and tweet about their common interest.
Reference REF proposed an efficient structurebased approach for detecting communities that share common interests on Twitter starting from celebrities representing an interest category.
A Topological Approach for Detecting Twitter Communities with Common Interests
MSM/MUSE
Political Science Computer Science