突发危机事件网络舆情治理的多情景演化博弈分析

doi:10.16381/j.cnki.issn1003-207x.2020.03.007

摘要/Abstract

摘要： 互联网时代，网络媒体已经成为谣言传播的重要载体，严重威胁到我国的网络空间安全和社会和谐稳定，因此加强和创新对网络媒体的监管，妥善治理突发危机事件网络舆情是各级政府面临的重大挑战。针对突发危机事件网络舆情治理的研究，本文运用演化博弈理论构建了网络媒体与地方政府双方演化博弈模型，在引入中央政府惩罚机制基础上，对比分析了网络媒体与地方政府双方行为策略选择的演化稳定均衡，同时采取多案例进行实证研究，并通过数值仿真分析对模型进行多情景推演模拟。研究结果表明：突发危机事件网络舆情传播热度与网络媒体和地方政府双方的策略选择有着直接关系；若地方政府承受突发危机事件网络舆情恶性演化造成的经济损失与信誉损失持续增大，双方演化系统都会出现周期性波动现象；引入中央政府惩罚机制后，其惩罚力度若高于网络媒体消极应对网络舆情所受到的惩罚和地方政府的监管投入成本时，最终系统会演化至良性状态，研究结论为政府部门在面对突发危机事件网络舆情治理方面提供了新思路。

关键词: 突发危机事件, 网络舆情, 政府治理, 演化博弈, 情景分析

Abstract: In the internet era, online media has become an important carrier of rumors spreading, which seriously threatens the safety and social harmony and stability of China's network space. Compared with traditional media, online media has become an important force for informational dissemination in emergencies, with its characteristics of large users, fast informational dissemination, and strong interactive function. Facing the complex network environment, what is the evolutionary equilibrium strategy of the local government and online media after repeated games? What are the key factors affecting the choice of local government and online media to respond to online public opinion strategies? How to realize the co-ordination of local governments and online media to cope with sudden crisis events by adjusting the central government punishment mechanism? These new problems are worth studying.
In this paper, considering the bounded rationality and information asymmetry of game subject, the evolutionary game theory is used to construct the evolutionary game model between the network media and the local government supervision department. Based on the introduction of the central government punishment mechanism, discussing the governance model of online public opinion,which is dominated by local government regulatory authorities and actively responded by online media.
Firstly, constructing an evolutionary game model of local government and online media in response to the behavioral strategy of sudden crisis events, and solving the evolutionary conditions of the network's public opinion heat propagation system to the local stable equilibrium state. Secondly, in order to make the system evolve to a rational state, the central government punishment mechanism is included in the above evolutionary game model. Establishing an extended evolutionary game model in which local governments and online media collaborate to manage network sentiment in sudden crisis events and derive the optimal evolution strategy of behavioral strategy choices between local governments and online media. Finally, the different types of sudden crisis are selected as research cases, and multiple scenarios are derived from the behavioral strategies of online media and local governments. The evolution and stability of the behavior strategies of the two parties under different scenarios are compared and analyzed.
The results of the study show that the public sentimental heat of sudden crisis events has a direct relationship with the choice of online media and local regulatory authorities. When the local government regulatory authorities are exposed to sudden crisis events, the economic losses and reputation losses caused by the vicious evolution of the network are constantly increasing, and the evolutionary systems of both sides will experience cyclical fluctuations. After the introduction of the central government punishment mechanism, if the punishment is higher than the punishment of the online media negatively responding to the Internet public opinion and the supervision input cost of the local government supervision department, and the system will ultimately evolve to a balance state.
The conclusion of the study is providing a new idea for government departments to solve the network public opinion in sudden crisis.

Key words: sudden crisis, online public opinion, government management, evolutionary game, scenario analysis

中图分类号:

C93.1

祁凯, 杨志. 突发危机事件网络舆情治理的多情景演化博弈分析[J]. 中国管理科学, 2020, 28(3): 59-70.

QI kai, YANG Zhi. Multi-scenario Evolutionary Game Analysis of Network Public Opinion Governance in Sudden Crisis[J]. Chinese Journal of Management Science, 2020, 28(3): 59-70.

参考文献

[1] 中国互联网信息中心. 第41次《中国互联网络发展状况统计报告》[EB/OL] http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201803/t20180305_70249.htm, 2018-07-20.
[2] 宗利永,顾宝炎.危机沟通环境中网络舆情演变的Multi-Agent建模研究[J].情报科学,2010,28(9):1414-1429.
[3] 祁明亮,池宏,赵红,等. 突发公共事件应急管理研究现状与展望[J].管理评论,2006,18(4):35-45.
[4] Jin Y, Liu B F, Austin L L. Examining the role of social media in effective crisis management:The effects of crisis origin, information form, and source on publics' crisis responses[J]. Communication research, 2014, 41(1):74-94.
[5] Wukich C. Social media use in emergency management[J]. Journal of Emergency Management, 2015, 13(4):281-294.
[6] Lachlan K A, Spence P R, Lin X, et al. Social media and crisis management:CERC, search strategies, and Twitter content[J]. Computers in Human Behavior, 2016, (54):647-652.
[7] Duggan F, Banwell L. Constructing a model of effective information dissemination in a crisis[J]. Information Research, 2004, 5(3):178-184.
[8] Schultz F, Utz S, G? ritz A. Is the medium the message? Perceptions of and reactions to crisis communication via twitter, blogs and traditional media[J]. Public relations review, 2011, 37(1):20-27.
[9] Yoo E, Rand W, Eftekhar M, et al. Evaluating information diffusion speed and its determinants in social media networks during humanitarian crises[J]. Journal of Operations Management, 2016, 45:123-133.
[10] Gil-García R, Pons-Porrata A. Dynamic hierarchical algorithms for document clustering[J]. Pattern Recognition Letters, 2010, 31(6):469-477.
[11] Koulouris A, Katerelos I, Tsekeris T. Multi-equilibria regulation agent-based model of opinion dynamics in social networks[J]. Interdisciplinary Description of Complex Systems, 2013,11(1):51-70.
[12] Regan A, Raats M D, Shan L C, Wall P G. Risk communication and social media during food safety crises:a study of stakeholders' opinions in Ireland[J]. Journal of Risk Research,2016,19(1):119-133.
[13] 陈海汉,陈婷. 突发事件网络舆情传播时段特征和政府预警模式研究[J].图书馆学研究,2015,(1):24-30.
[14] 宋宁,刘婵君. 过程与要素视角下的突发事件网络舆情演化规律研究[J].图书情报工作, 2016, 60(15):140-147.
[15] 李钢,陈璟浩. 突发公共事件网络舆情研究综述[J].图书情报知识,2014, (2):111-119.
[16] 董阳,陈晓旭.从"极化"走向"理性":网络空间中公共舆论的演变路径-百度百科"PX词条保卫战"的启示[J].公共管理学报,2015,12(4):55-67.
[17] 王光辉,刘怡君. 网络舆论危机事件的蔓延扩散效应研究[J]. 中国管理科学,2015, 23(7):119-126.
[18] 洪巍,史敏,洪小娟,等. 食品安全网络舆情中网民微博转发行为影响因素研究-以上海福喜事件为例[J]. 中国人口(资源与环境,2016, 26(5):167-176.
[19] 吴鹏,杨爽,张晶晶,等. 突发事件网络舆情中网民群体行为演化的Agent建模与仿真研究[J]. 现代图书情报技术,2015, (Z1):65-72.
[20] 余乐安,李玲,戴伟,等. 危化品水污染事件中政府危机信息公布策略与网络舆情扩散研究:基于多主体模型[J]. 管理评论,2016, 28(8):175-185.
[21] 韩普,王鹏. 基于无标度网络模型和传染病模型的舆论演化仿真研究[J].数据分析与知识发现,2017, (10):53-63.
[22] 陈福集,黄江玲.基于演化博弈的网络舆情传播的羊群效应研究[J].情报杂志,2013, 32(10):1-5.
[23] 宋彪,朱建明,黄启发. 基于群集动力学和演化博弈论的网络舆情疏导模型[J].系统工程理论与实践,2014, 34(11):2984-2994.
[24] 彭赓、熊烨明. 基于演化博弈的企业应对微博负面舆情策略研究[J].软科学,2016, 30(8):101-106.
[25] 李燕凌,丁莹. 网络舆情公共危机治理中社会信任修复研究-基于动物疫情危机演化博弈的实证分析[J].公共管理学报,2017, 14(4):91-101.
[26] 李勇建,王治莹. 突发事件中舆情传播机制与演化博弈分析[J].中国管理科学,2014, 22(11):87-96.
[27] 杨志,祁凯. 基于"情景-应对"的突发网络舆论事件演化博弈分析[J].情报科学,2018, 36(2):30-36.
[28] 李维安,王世权. 利益相关者治理理论研究脉络及其进展探析[J].外国经济与管理,2007, 29(4):10-17.
[29] 黄凯南. 演化博弈与演化经济学[J].经济研究,2009,(2):132-145.
[30] 刘人镜,孙滨,刘德海. 网络群体事件政府治理的演化博弈分析[J].管理学报,2015,12(6):911-919.
[31] 刘德海,韩呈军,尹丽娟. 城市拆迁群体性事件演化机理的多情景演化博弈分析[J].运筹与管理,2016,25(1):76-84.
[32] Friedman D.Evolutionary games in economics[J].Econometrical,1991,59(3):637-666.