A Node Importance Assessment Method for Complex Networks Based on the Neighborhood Influence

Abstract

Accurately assessing the contribution of neighbor nodes is of utmost importance for the evaluation of node importance. To further quantify the contribution of neighbor nodes to node importance, a node importance evaluation method based on the contribution refinement of multi-order neighbor node importance is constructed. This method comprehensively considers the independence and difference between same order neighbor nodes and utilizes the propagation mechanism of neighbor nodes' contributions. Then five real networks with different categories and structures are selected for propagation simulation experiments. The results show that the proposed algorithm has a higher ability to describe the node importance and identify the critical nodes in the network compared with the traditional metrics such as degree centrality, betweenness centrality, closeness centrality, and PageRank.