… -art in overlapping community detection algorithms, quality measures, … In addition to
community-level evaluation, we propose a … in a social network are naturally characterized by …

… In this paper, we present a novel network community detecting method based on the concept
of entropy and validate the accuracy of the method through simulation analysis. We also …

… In particular, we are given a social network consisting of (1) the social graph and (2) auxiliary
vertex information, in the form of attribute-value pairs assigned to each vertex in the graph. …

… vised clustering algorithm which is implemented in this work to emphasize community
detection in social network. The results specifies the number of high influence members …

… significance of game theory to social network analysis, here we provide a comprehensive
review of the available game theoretic literature for community detection in social networks. …

… Mark Newman [12] first introduces the concept of modularity for community detection in
the social network. The author presents a proficient methodology to maximize the modularity …

… In this paper, we propose an efficient algorithm OcdRank (Overlapping Community Detection
… can detect better community structures as compared to other existing community detection …

… need for new methods to detect and classify malware with … exploits community detection
properties and social network … conforming to community and social network properties and use …

… A community in a social network is defined as a set of nodes … network community detection
approaches. Section 3 includes details of the genetic algorithm used for community detection. …

… Abstract—Social network analysis has become a major … social network analysis is the
community detection problem, which can be seen as a graph clustering problem. However, social …