A Mathematical Optimization Model Designed to Determine the Optimal Timing of Online Rumor Intervention Based on Uncertainty Theory

Abstract

The multifaceted nature of online rumors poses challenges to their identification and control. Current approaches to online rumor governance are evolving from fragmented management to collaborative efforts, emphasizing the proactive management of rumor propagation processes. This transformation considers diverse rumor types, the response behaviors of self-media and netizens, and the capabilities of regulatory bodies. This study proposes a multi-agent intervention model rooted in uncertainty theory to mitigate online rumor dissemination. Its empirical validation includes comparing three rumor categories and testing it against a single-agent model, highlighting the efficacy of collaborative governance. Quantitative assessments underscore the model’s utility in providing regulatory authorities with a robust theoretical framework for adaptive decision-making and strategy adjustments based on real-world conditions.