Research on dynamic modeling and control mechanisms of rumor spread considering high-order interactions and counter-rumor groups
Qiao Zhou,
Xiaochang Duan and
Guang Yu
Chaos, Solitons & Fractals, 2025, vol. 197, issue C
Abstract:
Complex network theory has been widely applied to rumor propagation modeling and optimizing strategies. Nonetheless, most previous studies have been limited to binary interaction-based network topology, failing to differentiate the impact of various information types. This study proposes a dynamic rumor propagation model based on random simple complexes, integrating counter-rumor groups and higher-order interactions among heterogeneous groups. The proposed model establishes a finer-grained classification framework of rumor-exposed populations and information types (original posts and reposts), leveraging Markov Chain Monte Carlo sampling track the time-evolution of heterogeneous group proportions within empirically calibrated parameter ranges. Moreover, the study elucidates the higher-order coupling dynamics among multiple factors, including topological network metrics, debunking response latency, and collective suppression thresholds, with validation via the Weibo dataset. Results reveal that higher-order interactions accelerate rumor propagation speed; topological complexity and the debunking response rate have a dominant impact on the magnitude of rumor spread; whereas the number of initial counter-rumor nodes and global propagation scale constitute secondary contributing factors. In contrast to forwarding fact-checking information, the study reveals that focusing limited official resources on the production of original fact-checking content is more effective in inhibiting the spread of rumors. The finding is consistent with previous empirical studies. This study deepens comprehension of high-order interactions and behavior coupling in rumor and counter-rumor dissemination, providing practical methodological guidance for controlling irrational rumor dissemination.
Keywords: Rumor spreading; Debunking behavior; Higher-order interactions; Heterogeneous groups; Online social networks (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:197:y:2025:i:c:s0960077925005119
DOI: 10.1016/j.chaos.2025.116498
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