Ranking the Spreading Influence of Nodes in Complex Networks by Combining Local Average Weight and Average Normalized Link Entropy

Ranking the spreading influence of nodes is of great importance for controlling the spreading process on networks. Although a few measures are proposed for ranking nodes in weighted networks, it is still a challenge in accurately and efficiently ranking the spreading influence of nodes in weighted networks. In this paper, by utilizing both of the local and global topological structure information, a novel method is proposed. First, we define a local average weight (LAW) to describe the local topological structure information of nodes. Second, partly based on the link diversity, we define an average normalized link entropy (ANLE) to describe the global topological structure information of nodes. Further, by combining the LAW and ANLE, we propose a novel ranking measure termed as LAW-ANLE (LA) centrality. The proposed LA is verified by extensive experiments on a series of networks, and the results show that the LA is feasible and effective in accurately ranking the spreading influence of nodes.