Vital spreaders identification synthesizing cross entropy and information entropy with Kshell method

Identifying vital spreaders of complex networks is a crucial issue that studies the dynamic processes and analyzes the performance of networks. In this work, we present a new recognition method that not only takes into account the local property and global information, but also concerns the specific ranking order for high accuracy based on hierarchical structure. In this identification model, internal action and external action, which produced by constitution of the subnet structure in neighbors, are defined as forms of information entropy and cross entropy respectively. The main idea is to calculate the influentiality of a spreader through internal action and external action, and to design a specific ranks for optimizing the propagation effects and achieving promotion of precision. The proposed algorithm employs a series of indicators, including the monotonicity relation M, Susceptible-Infected-Susceptible(SIS) model, Kendall's coefficient z, spreading scale ratio S, average shortest path length Ls and computational complexity, to conduct experiments and assess the performance of networks. In comparison with other benchmark methods, the results of experiments illustrate its superiorities including rationality, efficiency and accuracy of spreading influence in different sized real-world networks.