Rumor source localization in social networks based on infection potential energy

Abstract

The location technology of information sources in social networks is a major factor in exploring the means of information propagation. In this context, most existing methods ignore the direction of infected nodes and fail to make full use of the diffusion information, resulting in poor identification of source localization. To address such problems, a novel source location method based on infection potential energy is proposed. Its methodology consists of several steps: Firstly, a network reconstruction method is suggested, based on infection potential energy, to make the constructed information diffusion path more accurate. Afterwards, a network pruning method is identified to reduce the search space of candidate sources. Finally, considering the minor differences in the Gaussian density values of multiple nodes and the tendency of the rumor to spread, a distance centrality method is proposed. Experiments in real networks show that the suggested method achieves a better location performance.