Overlapping community detection using superior seed set selection in social networks. (August 2018)

• Record Type: Journal Article
• Authors: R.V., Belfin; E., Grace Mary Kanaga; Piotr Bródka,
• Is Part Of: Computers & electrical engineering. Volume 70(2018)
• Page Start: 1074
• Page End: 1083
• Publication Date: 2018-08
• Subjects: Seed set -- Centrality -- Social network -- Overlapping community discovery -- Seed-centric; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.03.012
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Community discovery in the social network is one of the tremendously expanding areas which earn interest among researchers for past one decade. There are many already existing algorithms. However, new seed-based algorithms establish an emerging drift in this area. The basic idea behind these strategies is to identify exceptional nodes in the given network, called seeds, around which communities can be located. This paper proposes a blended strategy for locating suitable superior seed set by applying various centrality measures and using them to find overlapping communities. The examination of the algorithm has been performed regarding the goodness of the identified communities with the help of intra-cluster density and inter-cluster density. Finally, the runtime of the proposed algorithm has been compared with the existing community detection algorithms showing remarkable improvement.