Paper Title
Community Detection In Social Networks Based On Modularity Optimization

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.