演化博弈下化工突发事件网络舆情治理系统动力学分析

doi:10.16265/j.cnki.issn1003-3033.2025.02.2066

中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (2): 95-103.doi: 10.16265/j.cnki.issn1003-3033.2025.02.2066

演化博弈下化工突发事件网络舆情治理系统动力学分析

王晓庆¹^,²^,³(), 陈克兵¹^,^**(), 钱城江³^,⁴, 宋健⁵

¹ 南京航空航天大学经济与管理学院,江苏南京 211106
² 南京财经大学公共管理学院,江苏南京 210023
³ 南京财经大学红山学院工商管理系,江苏南京 211300
⁴ 南京南工应急科技有限公司,江苏南京 210032
⁵ 宿迁市宿城区住房和城乡建设局,江苏宿迁 223800

收稿日期:2024-09-17 修回日期:2024-11-24 出版日期:2025-02-28
通信作者:
**陈克兵(1978—),男,湖北荆州人,博士,教授,主要从事供应链管理、演化博弈等方面的研究。E-mail: kbchen@nuaa.edu.cn。
作者简介:
王晓庆 (1981—),男,江苏如东人,博士,高级工程师,主要从事数字经济与应急管理等方面的研究。E-mail: wxq@nufe.edu.cn。
钱城江高级工程师
宋健工程师
基金资助:
江苏省宿迁市2022年指导性科技计划项目(Z2022067)

System dynamics analysis of online public opinion governance for chemical emergencies under evolutionary games

WANG Xiaoqing¹^,²^,³(), CHEN Kebing¹^,^**(), QIAN Chengjiang³^,⁴, SONG Jian⁵

¹ College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing Jiangsu 211106, China
² College of Public Administration, Nanjing University of Finance & Economics, Nanjing Jiangsu 210023, China
³ Department of Business Administration, Nanjing University of Finance & Economics Hongshan College, Nanjing Jiangsu 211300, China
⁴ Nanjing NJTech Emergency Technology Co., Ltd.,, Nanjing Jiangsu 210032, China
⁵ Suqian Sucheng District Housing and Urban-Rural Development Bureau, Suqian Jiangsu 223800, China

Received:2024-09-17 Revised:2024-11-24 Published:2025-02-28

摘要/Abstract

摘要：

为加强化工突发事件网络舆情的治理,妥善处理因化工突发事件引发的网络舆情危机。将演化博弈理论引入网络舆情治理过程,构建地方政府和网络媒体的二元演化博弈模型,并结合系统动力学(SD)模型,构建地方政府和网络媒体的定量分析模型,根据相关案例开展模拟研究,对比分析各博弈主体的策略演化过程。结果表明:化工突发事件网络舆情热度取决于各主体的策略选择,演化博弈模型分析呈现出周期性反复趋势;引入惩罚机制后,适当提高惩罚力度可使得演化博弈系统进入良性状态;地方政府可通过提高网络舆情应急预警机制,加强对网络媒体的日常监管和协同治理工作,在应对化工突发事件网络舆情过程中合理制定惩罚措施可有效防止地方政府不作为、乱作为,实现对网络媒体的监管,避免网络舆情恶性演化。

关键词: 演化博弈, 化工突发事件, 网络舆情治理, 系统动力学(SD), 地方政府, 网络媒体

Abstract:

In order to strengthen the governance of online public opinion of chemical emergencies and properly handle the online public opinion crisis caused by chemical emergencies, evolutionary game theory was introduced into the process of network public opinion governance, and a binary evolutionary game model was constructed for local government and network media. Combined with the SD model, a quantitative analysis model was constructed for local governments and online media. Simulation research was conducted based on relevant cases, and the strategic evolution process of each game subject was compared and analyzed. The results indicate that the popularity of online public opinion on chemical emergencies depends on the strategic choices of each party, and the evolutionary game model analysis shows a periodic and recurrent trend. After introducing a punishment mechanism, appropriately increasing the severity of punishment can bring the evolutionary game system into a benign state. Local governments can enhance the emergency warning mechanism for online public opinion, strengthen daily supervision and collaborative governance of online media, and formulate reasonable punishment measures to effectively prevent local governments from inaction and disorderly behavior in the process of responding to chemical emergencies and online public opinion. This can achieve supervision of online media and avoid the vicious evolution of online public opinion.

Key words: evolutionary game, chemical emergencies, network public opinion governance, system dynamics (SD), local government, online media

中图分类号:

王晓庆, 陈克兵, 钱城江, 宋健. 演化博弈下化工突发事件网络舆情治理系统动力学分析[J]. 中国安全科学学报, 2025, 35(2): 95-103.

WANG Xiaoqing, CHEN Kebing, QIAN Chengjiang, SONG Jian. System dynamics analysis of online public opinion governance for chemical emergencies under evolutionary games[J]. China Safety Science Journal, 2025, 35(2): 95-103.

图/表 12

图1

表1

表2

局部均衡点的行列式与迹

(X,Y)	矩阵的行列式(det J₁)	矩阵的迹(tr J₁)
P₁(0,0)	(B+D-C+αE+αF)(G-H-αI+αJ)	(B+D-C+αE+αF)+(G-H-αI+αJ)
P₂(0,1)	(B-C)[-(G-H-αI+αJ)]	(B-C)+[-(G-H-αI+αJ)]
P₃(1,0)	(D+G-H)[-(B+D-C+αE+αF)]	(D+G-H)-(B+D-C+αE+αF)
P₄(1,1)	[-(B-C)][-(D+G-H)]	-(D+G-H)-(B-C)
P₅(X^,Y^)	$(α J - α I + G - H) (H - D - G) (B + D - C + α E + α F) (B - C) (D + α E + α F) (α J - α I - D)$	0

表2

表3

表4

表5

引入惩戒机制局部均衡点的行列式与迹

(X,Y)	矩阵的行列式(det J₁)	矩阵的迹(tr J₁)
P₁(0,0)	(B+D-C+αE+αF+K)(G-H-αI+ΑJ+K)	(B+D-C+αE+αF+K)+ (G-H-αI+αJ+K)
P₂(0,1)	(B-C+K)[-(G-H-αI+αJ+K)]	(B-C+K)+ [-(G-H-αI+αJ+K)]
P₃(1,0)	(D+G-H+K)[-(B+D-C+αE+αF+K)]	(D+G-H+K)- (B+D-C+αE+αF+K)
P₄(1,1)	[-(B-C+K)][-(D+G-H+K)]	-(D+G-H+K)- (B-C+K)
P₅(X^,Y^)	$(α J - α I + G - H + K) (H - D - G + K) (B + D - C + α E + α F + K) (B - C + K) (D + α E + α F) (α J - α I - D)$	0

表5

表6

图2

图3

图4

图5

图6

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博弈主体	地方政府
网络媒体	监管或应对策略	积极监管X	消极监管1-X
	积极应对Y	(A+B-C,G-H)	(A,G-H)
	消极应对1-Y	(B+D-C,-D)	[α(-E-F), α(I-J)]

(X,Y)	det J₁	tr J₁	分析结果
P₁(0,0)	+	-	ESS
P₂(0,1)	-	不确定	鞍点
P₃(1,0)	-	+	鞍点
P₄(1,1)	+	+	不稳定点
P₅(X^,Y^)	不确定	0	不稳定点

博弈主体	地方政府
网络媒体	监管或应对策略	积极监管X	消极监管1-X
	积极应对Y	(A+B-C, G-H)	(A-K,G-H)
	消极应对1-Y	(B+D-C, -D-K)	[α(-E-F)-K, α(I-J)-K]

(X,Y)	det J₁	tr J₁	分析结果
P₁(0,0)	+	+	不稳定点
P₂(0,1)	-	不确定	鞍点
P₃(1,0)	-	不确定	鞍点
P₄(1,1)	+	-	ESS
P₅(X^,Y^)	不确定	0	不稳定点

演化博弈下化工突发事件网络舆情治理系统动力学分析

System dynamics analysis of online public opinion governance for chemical emergencies under evolutionary games

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