HISBmodel: A rumor diffusion model based on human individual and social behaviors in online social networks

This paper attempts to address the rumor propagation problem in online social networks (OSNs) and proposes a novel rumor diffusion model, named the HISBmodel. Its originality lies in the consideration of various human factors such as the human social and individual behaviors and the individuals’ opinions. Moreover, we present new metrics that allow accurate assessment of the propagation of rumors. Based on this model, we present a strategy to minimize the influence of the rumor. Instead of blocking nodes, we propose to launch a truth campaign to raise the awareness to prevent the influence of a rumor. This problem is formulated from the perspective of a network inference using the survival theory. The experimental results illustrate that the HISBmodel depicts the evolution of rumor propagation more realistic than classical models. Moreover, Our model highlights the impact of human factors accurately as proven in the studies of the literature. Finally, these experiments showed the outstanding performance of our strategy to minimize the influence of the rumor by selecting precisely the candidate nodes to diminish the influence of the rumor.