Paper Title
Community Detection In Social Networks Based On Modularity Optimization
Abstract
Social networks are shown in graphs that divide into groups or communities of nodes with dense connections
within groups and sparser connections between them. Community detection is an important problem in social network
analysis. This paper uses a spectral method for increasing modularity. Modularity is a popular quality function to determine
the quality of a partition of a network. Spectral method using the eigenvector of modularity matrix could increase
modularity. The proposed method is tested on seven real networks. Experimental results show that our method has best
results based on modularity.
Keywords: Community Detection, Modularity, Social Networks, Spectral Method.