LAUSR

Quantitative identification of key nodes in complex networks is of great significance for studying the robustness and vulnerability of complex networks. Although various centralities have been proposed to solve this issue, each approach has its limitations for its own perspective of determining an actor to be “key”. In this paper, we propose a novel method to identify key nodes in complex networks based on global structure. Three aspects including the shortest path length, the number of shortest paths and the number of non-shortest paths are considered, and we establish three corresponding influence matrices. Node efficiency, which can reflect the contribution of one node to the information transmission of the entire network, is selected as the initial value of node’s influence on other nodes, and then the comprehensive influence matrix is constructed to reflect the influence among nodes. The proposed method provides a new measure to identify key nodes in complex networks from the perspective of global network structure, and can obtain more accurate identification results. Four experiments are conducted to evaluate the performance of our proposed method based on Susceptible–Infected (SI) model, and the results demonstrate the superiority of our method.