Overlapping community detection algorithm based on similarity of node relationship

Community discovery is a vital link in the research of social networks. Aiming at the shortcomings of the current local extension-based community discovery algorithm in local community discovery and extension, we propose a based on relationship similarity and local extension Overlapping community detection algorithm(RSLO). First, use the node's relationship similarity strategy to find close seed communities. Then, according to the discovered seed community, the similarity between the neighbor nodes of the community and the community is calculated, and the nodes whose similarity meets the threshold are selected. After that, an adaptive optimization function is used to expand the community. Finally, the free nodes that have not been divided into the community are divided into communities, thereby achieving a more comprehensive community discovery. We conduct experiments on classic datasets and artificially generated networks. The results show that the RSLO algorithm can find accurate and objective community structures.