An Enhanced Network Density Based Centrality for Influential Node Detection in Complex Networks

Comprehending the dynamics of disease or information diffusion requires influential node detection in complex networks. Numerous centrality measures were developed for calculating the spreading capacity of a node. However, they fail to produce a high monotonic ranking of spreaders, which is a highly desired property. Two new measures, local density and extended local density are introduced in this paper to calculate the spreading impact of every node using the density of edges in the neighborhood of the node and the node degree. Our experimental results demonstrate that both of our proposed metrics offer a more consistent monotonic result for node ranking and better rank distribution than other centrality measures.