In this paper, we propose a unified framework OCTracker for tracking overlapping community evolution in online social networks. OCTracker adapts a preliminary community structure towards dynamic changes in social networks using a novel density-based approach for detecting overlapping community structures and automatically detects evolutionary events like birth, growth, contraction, merge, split, and death of communities with time. Unlike other density-based community detection methods, the proposed method does not require the neighborhood threshold parameter to be set by the users, rather it automatically determines the same for each node locally.
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Bhat et al. (2012) studied this question.
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