Hidden influential node selection based on cost–benefit analysis for harmful information propagation control

Abstract

The quick development of mobile network and smart devices provides a convenience way for information sharing in online social networks, which also accelerates the propagation of harmful information, thus how to select the hidden influential nodes with lower management cost for reducing the propagation speed of harmful information is an important task. In this article, we propose a greedy hidden influential node selection algorithm based on the epidemic model and cost–benefit analysis. First, we investigate the user behaviour dynamic characteristics from two perspectives of social relationships and interaction behaviours, and then susceptible and infected (SI) epidemic model is applied and user influence is estimated. Second, considering the management cost and benefit of different users, a greedy hidden influential node selection algorithm based on the cost–benefit analysis is proposed. Finally, a series of experiments are conducted using the public social network data set and the data set collected from Sina Weibo, to verify the performance and practicality of the developed method. The experimental results demonstrate that our method outperforms other related methods in harmful information propagation control.