基于Multi-Agent的政府干预下虚假舆情传播规律与控制决策
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摘要
[目的 /意义]为研究政府干预对虚假舆情传播的影响。[方法 /过程]首先,基于个体异质性,将群众进行分类,分析了各类群众之间的状态转移关系;然后,借鉴Bass模型,构建了在政府干预下虚假舆情传播扩散的数学模型;第三,使用Multi-Agent技术构建了群众状态转化逻辑关系来模拟仿真虚假舆情传播的规律;最后,考察了政府干预时间与干预强度对群众行为状态转化的影响。[结论 /结果]经过理论建模和仿真分析验证了本文预测方法的有效性和可行性,将为政府准确把握虚假舆情传播规律、有效防控虚假舆情扩散蔓延提供理论依据。
[Purpose/Significance] To research the influence of Propagation of false public opinion under the government intervention. [Method/Procedure] Firstly,based on individual heterogeneity,the masses were classified and the state transition relations among various masses were analyzed. Then,utilizing Bass model,the mathematical model was built for diffusion of false public opinion under intervention of government. Furthermore,the logical relation of mass state transformation was constructed by Multi-Agent technique,which simulated the law of the Propagation of false public opinion. Finally,the influence for state transformation of mass behavior was analyzed through governmental intervention time and intervention intensity. [Conclusion/Result] The prediction method was feasible by theoretical modeling and simulated analysis. The above theory research could make government accurately grasp Propagation law of false public opinion and provide references for government to make related policies
[Purpose/Significance] To research the influence of Propagation of false public opinion under the government intervention. [Method/Procedure] Firstly,based on individual heterogeneity,the masses were classified and the state transition relations among various masses were analyzed. Then,utilizing Bass model,the mathematical model was built for diffusion of false public opinion under intervention of government. Furthermore,the logical relation of mass state transformation was constructed by Multi-Agent technique,which simulated the law of the Propagation of false public opinion. Finally,the influence for state transformation of mass behavior was analyzed through governmental intervention time and intervention intensity. [Conclusion/Result] The prediction method was feasible by theoretical modeling and simulated analysis. The above theory research could make government accurately grasp Propagation law of false public opinion and provide references for government to make related policies
引文
[1]王治莹,李勇建.政府干预下突发事件舆情传播规律与控制决策[J].管理科学学报,2017,20(2):43-52.
[2]王世雄,潘旭伟,姜毅.基于线上线下互动网络的社会共识涌现研究[J].情报杂志,2017,36(3):67-73.
[3]谢科范,赵湜,陈刚,等.网络舆情突发事件的生命周期原理及集群决策研究[J].武汉理工大学学报:社会科学版,2010,23(4):482-486.
[4]辛文娟,赖涵.群体极化视域下网络舆情的演化机制研究——以微博网民讨论“浙江温岭杀医案”为例[J].情报杂志,2015,34(2):47-52.
[5]于兆吉,张嘉桐.基于扎根理论的突发性网络舆情演化影响因素研究[J].东北大学学报:社会科学版,2016,18(5):498-502.
[6]李昊青.基于信息异化理论的网络衍生舆情演化规律及对策研究——以网络谣言治理为例[J].现代情报,2015,35(5):4-8.
[7]兰月新,邓新元.突发事件网络舆情演进规律模型研究[J].情报杂志,2011,(8):47-50.
[8]张一文,齐佳音,马君,等.网络舆情与非常规突发事件作用机制——基于系统动力学建模分析[J].情报杂志,2010,29(9):1-6.
[9]Kim K,Baek Y M,Kim N.Online News Diffusion Dynamics and Public Opinion Formation:A Case Study of the Controversy Over Judges'Personal Opinion Expression on SNS in Korea[J].Social Science Journal,2015,52(2):205-216.
[10]石彭辉.基于社会网络分析的网络舆情实证研究[J].现代情报,2013,33(2):27-31.
[11]方薇,何留进,孙凯,等.采用元胞自动机的网络舆情传播模型研究[J].计算机应用,2010,30(3):751-755.
[12]韩少春,刘云,张彦超,等.基于动态演化博弈论的舆论传播羊群效应[J].系统工程学报,2011,26(2):275-281.
[13]Freeman M,Mcvittie J,Sivak I,et al.Viral Information Propagation in the Digg Online Social Network[J].Physica A Statistical Mechanics&Its Applications,2014,415(415):87-94.
[14]王靖元,张鹏,刘立文,等.网络谣言传播效能评价研究[J].情报杂志,2016,35(1):105-109.
[15]陈艳红,杜艺薇.虚假网络舆情的成因、影响及控制[J].电子政务,2016,(5):68-75.
[16]林寒.网络虚假事件传播的理论解释和现实逻辑——基于热点事件“上海女逃离江西农村”的舆情分析[J].北京理工大学学报:社会科学版,2016,18(5):151-157.
[17]兰月新.突发事件网络谣言传播规律模型研究[J].图书情报工作,2012,56(14):57-61.
[18]孙雷霆,李春发,陶建强.基于Multi-Agent的虚假舆情传播仿真[J].情报杂志,2017,36(4):162-169.
[19]崔鹏,张巍,何毅,等.突发公共事件网络舆情演化及政府应对能力研究[J].现代情报,2018,38(2):75-83.
[20]Bass,F.M.A New Product Growth Model for Consumer Durables[J].Management Science,1969,15(1),215-227.
[2]王世雄,潘旭伟,姜毅.基于线上线下互动网络的社会共识涌现研究[J].情报杂志,2017,36(3):67-73.
[3]谢科范,赵湜,陈刚,等.网络舆情突发事件的生命周期原理及集群决策研究[J].武汉理工大学学报:社会科学版,2010,23(4):482-486.
[4]辛文娟,赖涵.群体极化视域下网络舆情的演化机制研究——以微博网民讨论“浙江温岭杀医案”为例[J].情报杂志,2015,34(2):47-52.
[5]于兆吉,张嘉桐.基于扎根理论的突发性网络舆情演化影响因素研究[J].东北大学学报:社会科学版,2016,18(5):498-502.
[6]李昊青.基于信息异化理论的网络衍生舆情演化规律及对策研究——以网络谣言治理为例[J].现代情报,2015,35(5):4-8.
[7]兰月新,邓新元.突发事件网络舆情演进规律模型研究[J].情报杂志,2011,(8):47-50.
[8]张一文,齐佳音,马君,等.网络舆情与非常规突发事件作用机制——基于系统动力学建模分析[J].情报杂志,2010,29(9):1-6.
[9]Kim K,Baek Y M,Kim N.Online News Diffusion Dynamics and Public Opinion Formation:A Case Study of the Controversy Over Judges'Personal Opinion Expression on SNS in Korea[J].Social Science Journal,2015,52(2):205-216.
[10]石彭辉.基于社会网络分析的网络舆情实证研究[J].现代情报,2013,33(2):27-31.
[11]方薇,何留进,孙凯,等.采用元胞自动机的网络舆情传播模型研究[J].计算机应用,2010,30(3):751-755.
[12]韩少春,刘云,张彦超,等.基于动态演化博弈论的舆论传播羊群效应[J].系统工程学报,2011,26(2):275-281.
[13]Freeman M,Mcvittie J,Sivak I,et al.Viral Information Propagation in the Digg Online Social Network[J].Physica A Statistical Mechanics&Its Applications,2014,415(415):87-94.
[14]王靖元,张鹏,刘立文,等.网络谣言传播效能评价研究[J].情报杂志,2016,35(1):105-109.
[15]陈艳红,杜艺薇.虚假网络舆情的成因、影响及控制[J].电子政务,2016,(5):68-75.
[16]林寒.网络虚假事件传播的理论解释和现实逻辑——基于热点事件“上海女逃离江西农村”的舆情分析[J].北京理工大学学报:社会科学版,2016,18(5):151-157.
[17]兰月新.突发事件网络谣言传播规律模型研究[J].图书情报工作,2012,56(14):57-61.
[18]孙雷霆,李春发,陶建强.基于Multi-Agent的虚假舆情传播仿真[J].情报杂志,2017,36(4):162-169.
[19]崔鹏,张巍,何毅,等.突发公共事件网络舆情演化及政府应对能力研究[J].现代情报,2018,38(2):75-83.
[20]Bass,F.M.A New Product Growth Model for Consumer Durables[J].Management Science,1969,15(1),215-227.