A Label Propagation Algorithm based on Similarity and Weighted

The research on complex networks has been a hotspot in many fields, among which community structure is a common feature in complex networks. The whole network is composed of many communities, and the connections between nodes in the same community are very tight, while the connections between communities are relatively sparse. In this context, this paper focuses on a SWLPA (Similarity and Weighted Based Label Propagation Algorithm) label propagation algorithm based on similarity and neighbor node weight. This paper first calculates the probability of label propagation according to the similarity between nodes and the weight of neighbor nodes, then filters labels according to the influence of each node and carries out label propagation, and finally gets the result of community division. The experimental result shows that the method effectively improved the accuracy of community division results.