Community Detection Algorithm based on Node Similarity in Signed Networks

Hierarchical clustering algorithms based on node similarity have been widely used in community detection, but it is not suitable for signed networks. The typical signed network community detection algorithm has the problem of low community division rate from different nodes. Based on the similarity of nodes, this paper proposes the CDNS algorithm (Community Detection Algorithm based on Node Similarity in Signed Networks). Firstly, the algorithm proposes a node influence measure suitable for signed networks as the basis for selecting the initial node of the community. Secondly, it proposes the calculation of the node similarity based on the eigenvector centrality, and selects the node with the highest similarity from the initial node from the neighbour nodes to form the initial community. Finally, according to the community contribution of neighbour nodes, algorithm determines whether the neighbour nodes are joined in the community and in which order the neighbour nodes are joined in the community. The experiments of real signed network and simulated signed network prove that the CDNS algorithm has good accuracy and efficiency.