| 摘 要: 在信息快速传播的数字时代,谣言的扩散对社会稳定与公众认知产生深远影响。传统谣言传播模型往往忽略个体异质性和认知差异等关键因素,难以精准刻画现实社交网络中的传播动态。基于此,在SEIR谣言传播模型基础上,提出了一种S2EIR谣言传播模型,将未知者细分为受教育程度高、低的群体。通过数学建模、动力学分析推导谣言传播阈值,用龙格-库塔法求解方程,并在 WS、BA 及 Facebook 网络上仿真。结果显示,Facebook网络中谣言传播最快,而提高受教育程度高群体的比例能显著降低传播者峰值密度。此外,降低传播率、提高免疫率和遗忘率也能有效抑制谣言传播。 |
| 关键词: 复杂网络 谣言传播 受教育程度 怀疑机制 |
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| Research on Rumor Propagation Considering Educational Differences and Skepticism Mechanism |
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LIN Ziyi, WANG Youguo, ZHAI Qiqing
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(College of Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)
1916314529@qq.com; wangyg@njupt.edu.cn; qiqingzhai@163.com
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| Abstract: In the digital era of rapid information dissemination, the spread of rumors has profound impacts on social stability and public perception. Traditional rumor propagation models often overlook key factors such as individual heterogeneity and cognitive differences, making it difficult to accurately depict the dynamics of dissemination in rea-l world social networks. To address this, based on the SEIR rumor propagation model, this study proposes an S2EIR rumor propagation model that further divides the unaware population into groups with high and low levels of education. Through mathematical modeling and dynamic analysis, the propagation threshold is derived, and the equations are solved using the Runge-Kutta method. Simulations are conducted on WS network, BA network, and Facebook network. The results show that rumor spread is fastest in the Facebook network, and increasing the proportion of highly educated individuals significantly reduces the peak density of spreaders. In addition, reducing the
transmission rate, increasing the immunity rate, and increasing the forgetting rate can also effectively suppress thespread of rumors. |
| Keywords: complex networks rumor propagation educational level skepticism mechanism |
