Exploring the dynamics of group-based internet rumors propagation: A novel model from the perspective of random hypergraphs

Abstract

Group interactions have become an important way of online communication today. In this paper, a novel random Hyper-ISDR rumor model is proposed, which uses random hypergraphs to describe the group relationship more accurately. A key innovation of our model is the introduction of hyperpath and path indicators into the group propagation characterization for the first time, explaining the multiple path selectivity present in group propagation. Then, the theoretical conditions for the disappearance and persistence of Internet rumors are obtained by applying stochastic stability theory. This paper finds three interesting results: (1) the propagation threshold on hypergraphs is more sensitive to parameter changes than on traditional graphs; (2) the multiple selectivity of the group propagation path is a critical catalyst for swift rumor diffusion; (3) educating spreaders to become refuters rather than removers is more effective in controlling rumors. Moreover, compared with the graph-based ISDR model and the Hyper-SIR model, it shows that the hyperdegree and path indicators have a greater impact on rumor volatility. Finally, the reliability and applicability of the results are verified by numerical simulation and a real-life case study. This work not only opens up a new perspective of group rumor dynamics analysis, but also provides a superior framework for understanding and managing online information diffusion.