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

Meiling Jin, Fengming Liu, Yufu Ning, Yichang Gao and Dongmei Li ()
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Meiling Jin: School of Management, Shanghai University, Shanghai 200444, China
Fengming Liu: Business School, Shandong Normal University, Jinan 250014, China
Yufu Ning: School of Information Engineering, Shandong Youth University of Political Science, Jinan 250103, China
Yichang Gao: Artificial Intelligence and Cyber Futures Institute, Charles Sturt University, Bathurst, NSW 2795, Australia
Dongmei Li: School of Management, Shanghai University, Shanghai 200444, China

Mathematics, 2024, vol. 12, issue 16, 1-21

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.

Keywords: uncertainty theory; multi-agent intervention model; timing of intervention; decision making; online rumor (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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