关键词: rumor suppression, adaptive regulation, social network, propagation dynamics

Abstract: Regulation plays a pivotal role in mitigating the spread of rumors, serving as a vital tool for maintaining social stability and facilitating its evolution. A central challenge lies in establishing an effective regulatory framework despite limited resources available for combating rumor propagation. To address this challenge, this paper proposes a dynamic and adaptive regulatory system. First, based on observed regulatory patterns in real-world social networks, the rumor propagation process is divided into two distinct phases: regulation and intervention. Regulatory intensity is introduced as an indicator of user state transitions. Unlike traditional, non-adaptive regulatory models that allocate costs uniformly, the adaptive model facilitates flexible cost distribution through a manageable individual regulatory intensity. Moreover, by introducing adaptive strength, the two cost allocation models are integrated within a unified framework, leading to the development of a dynamic model for rumor suppression. Finally, simulation experiments on Barabási-Albert (BA) networks demonstrate that the adaptive regulatory mechanism significantly reduces both the scope and duration of rumor propagation. Furthermore, when traditional non-adaptive regulatory models show limited effectiveness, the adaptive model effectively curbs rumor propagation by optimizing cost allocation between regulatory and intervention processes, and by adjusting per-unit cost benefit differentials.

Key words: rumor suppression, adaptive regulation, social network, propagation dynamics