Identify influential nodes in complex networks based on modified TOPSIS

In complex networks, identifying influential nodes is the very important issue, which has a wide range of applications. In this paper, factor analysis method is used to mine the relationships of multiple metric measurements, and then a new evaluation method of node importance in complex networks based on modified technique for order performance by similarity to ideal solution (TOPSIS) approach is proposed. TOPSIS is utilized to aggregate the multi-attribute to obtain the evaluation of node importance of each node. The more centrality measures considered, the more results more exact and effective. Then, we use the SIS model to evaluate the performance. The experiment result is showed that out method have more the efficiency and practicability than the proposed method.