Weighted k-shell decomposition for complex networks based on potential edge weights

Identifying influential nodes in complex networks has attracted much attention because of its great theoretical significance and wide application. Existing methods consider the edges equally when designing identifying methods for the unweighted networks. In this paper, we propose an edge weighting method based on adding the degree of its two end nodes and for the constructed weighted networks, we propose a weighted k-shell decomposition method (Wks). Further investigations on the epidemic spreading process of the Susceptible-Infected-Recovered (SIR) model and Susceptible-Infected (SI) model in real complex networks verify that our method is effective for detecting the node influence.