A new method for identifying influential nodes based on D-S evidence theory

In complex networks, how to identify influential nodes in complex networks is a hot topic. Recently, weights of nodes and degree of nodes are combined for identifying influential nodes in the weighted networks. Degree centrality, closeness centrality and betweenness centrality are the most basic measures for describing the influence of nodes. In this paper, degree centrality, closeness centrality and betweenness centrality are considered. The three measures are built three basic probability assignment (BPAs) based on evidence theory, respectively. Then, a final measure, which is used to identify influence of nodes, is obtained by combining the three BPAs. Numerical examples are used to illustrate the effectiveness of the proposed method.