Identifying influential nodes in weighted networks based on evidence theory

The design of an effective ranking method to identify influential nodes is an important problem in the study of complex networks. In this paper, a new centrality measure is proposed based on the Dempster–Shafer evidence theory. The proposed measure trades off between the degree and strength of every node in a weighted network. The influences of both the degree and the strength of each node are represented by basic probability assignment (BPA). The proposed centrality measure is determined by the combination of these BPAs. Numerical examples are used to illustrate the effectiveness of the proposed method.

► A new centrality metric is proposed to identify influential nodes.
► The influences of both the edge weight and the node degree are taken into consideration.
► Dempster–Shafer evidence theory is used to combine the edge weight and node degree.
► Experimental results indicate that the proposed metric can well identify influential nodes.