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突发公共事件网络谣言传播长尾效应的控制研究——以新型冠状病毒肺炎疫情为例
更新日期:2021-05-18     浏览次数:145
核心提示:摘要[目的/意义]关注突发公共卫生事件网络谣言长尾传播现象,从博弈角度探求长尾的控制变量,为实现网络谣言治理长效化提供依据。[方法/过程]基于官方辟

摘要 [目的/意义]关注突发公共卫生事件网络谣言"长尾"传播现象,从博弈角度探求"长尾"的控制变量,为实现网络谣言治理长效化提供依据。[方法/过程]基于官方辟谣后信息生态环境和公众认知的差异,引入SIRS模型,以不完全信息动态博弈为基础构建传播模型,计算出长尾期个体策略分布,利用MATLAB进行仿真和案例验证,寻找"长尾"控制途径。[结果/结论]长尾控制博弈模型分析从个体交互层面为网络谣言管控带来新思路。在突发公共卫生事件网络谣言传播后期,作为拽尾策略,增加个体不信谣的收益、降低个体的谣言相关信息分析成本均需被持续实践。其中,比之于增加公共收益,增加不信谣的个体收益有更大的长尾控制效用,是重点关注工作。 [Purpose/significance]This paper focuses on the phenomenon of"long tail"spread of Internet rumors in public health emergencies,and explores the control variables of"long tail"from the perspective of Game Theory,so as to provide a basis for the long-term and effective governance of internet rumors.[Method/process]Introducing the SIRS model based on the difference of information ecological environment and public cognition after official refutation of the rumors.Constructing the spreading model based on the dynamic game of incomplete information and calculating the individual strategy distribution in the long-tail period.Looking for ways to control the long tail by using MATLAB to carry on the simulation check computation and the case verification.[Result/conclusion]The analysis of the Long-tail Control Game Model brings new ideas for the management and control of Internet rumors from the level of individual interaction.In the late stage of Internet rumor spreading,as a tail-pulling strategy,it is necessary to increase the benefits of disbelieving rumors and reduce the cost of analyzing rumours-related information.Compared to increasing the public revenue,to increase the income of individuals who do not believe the rumor has greater long-tail control effect.It should be highlighted.
作者 张桂蓉 夏霆 Zhang Guirong(不详)
出处 《情报理论与实践》 北大核心 2021年第3期69-75,共7页 Information Studies:Theory & Application
基金 2020年中南大学前沿交叉专项基金项目“重大传染病疫情应急体系的触发与运行机制研究” 2020年中南大学研究生自主探索创新项目“突发公共卫生事件中政府舆情控制研究”(项目编号:2020ZZTS310)的成果。
关键词 新型冠状病毒肺炎疫情 网络谣言 长尾效应 SIRS模型 不完全信息动态博弈 COVID-19 Internet rumors long-tail effect SIRS model dynamic game of incomplete information