Rumor Propagation and Supervision during Confrontation: An Importance-Driven SIRQS Network Model

TL;DR

This paper introduces a novel rumor propagation model incorporating confrontation and supervision mechanisms, emphasizing the importance of targeted monitoring and individual state differences in controlling rumor spread.

Contribution

It extends the classical SIRS model to include confrontation and supervision, providing a new framework for understanding rumor dynamics and control strategies.

Findings

Supervision effectiveness depends on the number of supervisors and confrontation mechanisms.

Targeted patrols guided by node importance improve rumor containment.

Simulation results highlight key factors influencing rumor control in various network topologies.

Abstract

The societal impact of rumor spreading is becoming increasingly severe; yet, current research remains relatively one-sided, typically focusing on either rumor propagation or rumor control while neglecting the confrontational and dynamically evolving relationship between them. To address this gap, we propose a novel confrontation framework for rumor modeling. We extend the classical Susceptible-Infected-Recovered-Susceptible (SIRS) model into an Ignorant-Spreader-Stifler-Vigilant-Ignorant (SIRQS) framework by introducing a vigilant state and a confrontation mechanism, thereby capturing subtle differences in individual states during rumor propagation and in their confrontational behavior toward supervisors. At the same time, supervisors patrol the network through random walks guided by node propagation importance, enabling targeted monitoring of rumor spreaders and individuals with a high risk of spreading rumors. Using a microscopic Markov chain approach, we further characterize heterogeneous node behavior and individual differences, and couple the propagation and supervision processes to model node-state transition patterns. We conduct simulations on networks with three different sizes, various topologies, and a real-world network. The results show that the supervision subject, the preference effects associated with the number of supervisors, and the confrontation mechanism are key factors in supervision, and largely determine the effectiveness of rumor propagation control in the simulations, reflecting the substantial influence of these three mechanisms in real-world spreading scenarios. Finally, through multiple evaluation indicators, we provide references for determining the optimal number of supervisors.