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

Overlapping community detection using superior seed set selection in social networks