摘要
【目的/意义】建立新的网络谣言传播模型,为网络谣言的应对及治理提供有益的参考。【方法/过程】针对网络谣言的传播特点,借鉴药物动力学中的药物扩散原理,建立了网络谣言的CFDR传播模型,给出了相应的数学方程式;进一步探讨了权威媒体干预因素和时滞性影响,对模型进行了优化,修正了谣言传播的峰值预测和总人数值;利用matlab、python等工具进行对参数的敏感性进行了分析;最后,以“成都49中”事件为实例验证了模型的有效性,并分析了相关影响因素。【结果/结论】结果表明:利用CFDR模型可以较好地拟合网络谣言传播的全过程,模型的各参数对网络谣言的传播都有影响,其中,权威媒体的正向干预在网络谣言的传播过程中发挥着重要作用。【创新/局限】创新性主要体现在:突破以往基于传染病动力学模型研究网络舆情和谣言传播的固有模式,借鉴药物扩散原理建立了网络谣言CFDR传播模型,并考虑了权威媒体干预因素和时滞性影响。局限性主要表现为:实例验证中只使用了一个事件中一个平台的实际数据,未来可进一步丰富。
【Purpose/significance】To establish a new propagation model of network rumor,and provide useful reference for dealing with and managing network rumor.【Method/process】According to the propagation characteristics of network rumor,the CFDR propagation model of network rumor was established by the principle of drug diffusion in pharmacokinetics,and the corresponding mathematical equations were given.Furthermore,considering the influence of authoritative media and time delay,the model is optimized,and the peak prediction and total number of rumor propagation are revised.The sensitivity of parameters is analyzed by using Matlab,Python and other tools.Finally,the"Chengdu 49 Middle School"event is taken as an instance to verify the validity of the model,and the relevant influencing factors are analyzed.【Result/conclusion】The results show that the CFDR model can be used to better fit the whole process of network rumor propagation,and all parameters of the model have an impact on the spread of network rumor.Among them,the positive intervention of authoritative media plays an important role in the spread of network rumor.【Innovation/limitation】The innovation is mainly reflected in:breaking through the previous inherent mode of studying network public opinion and rumor propagation based on infectious disease dynamics model,establishing CFDR network rumor propagation model by referring to drug diffusion principle,and considering the intervention factors of authoritative media and the influence of time delay.The main limitation is as follows:only the actual data of one platform in one event is used in the instance verification,which can be further enriched in the future.
作者
李延晖
姚琪
魏雅婷
曾江峰
LI Yan-hui;YAO Qi;WEI Ya-ting;ZENG Jiang-feng(School of Information Management,Central China Normal University,Wuhan 430079,China;Management School,Wuhan College,Wuhan 430212,China)
出处
《情报科学》
CSSCI
北大核心
2022年第10期33-42,106,共11页
Information Science
基金
国家自然科学基金青年项目“情感感知的可解释虚假新闻检测研究”(62102159)
教育部人文社会科学研究青年基金项目“情景大数据驱动的社交媒体虚假信息识别模型与治理策略研究”(21YJC870002)
