摘要
[目的/意义]突发公共卫生事件期间,网民内生健康信息需求的同时缺乏健康信息的科学知识,为造谣者发布和传播网络谣言提供了机会。无效的科学知识及虚假新闻会对流行病爆发期间的社会稳定产生严重负面影响,扰乱社会秩序。因此构建有效的网络谣言传播-逆转模型以控制网络谣言的传播并降低其负面影响极为重要。[方法/过程]研究采纳科学知识水平理论与网络谣言辟谣策略,基于SIR模型构建SCNDR网络谣言逆转系统动力学模型。采纳Anylogic软件对提出的SCNDR模型进行模拟仿真,并对模型的参数进行敏感性分析,提出了提升网络谣言传播-逆转模型逆转效率的具体策略。[结果/结论]研究提出的SCNDR模型有效模拟了突发公共卫生事件期间网络谣言的传播-逆转过程,影响网络谣言逆转效率的关键因素分别为用户科学知识水平普及率、官方辟谣信息公开时间及轻信节点转化效率。
[Purpose/significance]During public health emergencies,due to folks'endogenous demand for health information and lack of scientific knowledge of health information,it stimulates the mass media to spread health information,and also provides opportunities for rumors to publish and spread online rumors.Ineffective scientific knowledge and false news will have a serious negative impact on social stability and disrupt social order during the outbreak of epidemics.Therefore,it is very important to build an effective reversal model of online rumor propagation to control the spread of online rumors and reduce its negative impact.[Method/process]The research adopted the theory of scientific knowledge level and the strategy of online rumors reputation,and constructed the SCNDR online rumor reversal model based on SIR model.The Anylogic software was adopted to simulate the SCNDR model,and the sensitivity analysis of the parameters of the model was carried out.[Result/conclusion]The SCNDR model proposed in this study effectively simulates the reversal process of online rumors during public health emergencies.The key factors affecting the reversal efficiency of online rumors are the penetration rate of users'scientific knowledge level,the public time of official information and the conversion efficiency of credulous users.
作者
王晰巍
李玥琪
邱程程
胡欢
Wang Xiwei;Li Yueqi;Qiu Chengcheng;Hu Huan(School of Management,Jilin University,Changchun 130022;Research Center for Big Data Management,Jilin University,Changchun 130022;Research Center of Cyberspace Governance,Jilin University,Changchun 130022;School of Economics and Management,Jiangxi University of Science and Technology,Ganzhou 341000)
出处
《图书情报工作》
CSSCI
北大核心
2021年第19期3-15,共13页
Library and Information Service
基金
国家社会科学基金重大项目“大数据驱动的社交网络舆情主题图谱构建及调控策略研究”(项目编号:18ZDA310)
吉林大学国家发展与安全(生物安全)专项研究课题“生物安全风险治理的舆论传播体系研究(重点课题)”研究成果之一。
