This paper proposes an individual-based mean-field model for fake news spreading on the PSO-based networks, assuming that ignorant individuals are more likely to believe and repost the fake news that are spread by the similar spreaders. Therefore, the spreading rate is related to the similarity between these individuals. Theoretical analysis shows that the critical threshold is in inverse proportion to both the maximum eigenvalue of the similarity matrix and the influence coefficient [Formula: see text]. Monte-Carlo simulations are performed on the PSO-based networks, demonstrating the effectiveness of the proposed model.

中文翻译：

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基于个体的平均场模型，用于在基于 PSO 的网络上传播假新闻

本文提出了一种基于个人的平均场模型，用于在基于 PSO 的网络上传播假新闻，假设无知的个人更有可能相信并转发由类似传播者传播的假新闻。因此，传播率与这些个体之间的相似性有关。理论分析表明，临界阈值与相似矩阵的最大特征值和影响系数成反比[公式：见正文]。蒙特卡罗模拟在基于 PSO 的网络上进行，证明了所提出模型的有效性。