面向舆情治理的信息管理机制演化博弈模型

doi:10.11959/j.issn.2096-109x.2023086

Abstract

Abstract:

Conflicting information in online social networks, often stemming from opposing views, can lead to rumors and the fragmentation of society.A reputation-based dynamic information management mechanism was proposed, adopting a dynamic reward and punishment strategy to decrease unnecessary information conflict so as to activate self-purification of network.By utilizing evolutionary game theory, a cumulative-prospect-based evolutionary game model of social network information conflict was constructed to validate the efficacy of the proposed mechanism.Numerical simulations were conducted to analyze the evolutionary trends of 18 different theoretical application scenarios under 9 constraints.The results demonstrate that, under constraint 5, both sides of the game tend to exhibit relatively rational behavior towards conflicts.Furthermore, dynamic evolution analysis and sensitivity analysis of the model parameters were performed while satisfying constraint 5, providing practical strategic suggestions for the dynamic information management mechanism.This model represents a novel attempt to capture the interaction of multiple factors, such as interest-driven behavior and conformity psychology, in the evolution of public opinion.Moreover, the model successfully simulates well-known patterns of rumor dissemination, confirming its validity.The proposed model offers valuable insights for the development and design of malicious information control systems in social networks and provides new ideas for the research and implementation of public opinion governance.

Key words: evolutionary game, information management, reputation, social network, public opinion governance

CLC Number:

TP393

Shuting LIU, Yinghua MA, Xiuzhen CHEN. Evolutionary game model of information management mechanism for public opinion governance[J]. Chinese Journal of Network and Information Security, 2023, 9(6): 102-115.

Figures/Tables 12

均衡解	$\det (J)$	$tr (J)$
F₁	$\begin{array}{l} λ^{2} E_{1} (K_{1} + C_{1})^{β} \\ (K_{2} + C_{2})^{β} \end{array}$	$\begin{array}{l} λ [E_{1} (K_{1} + C_{1})^{β} + \\ (K_{2} + C_{2})^{β}] \end{array}$
F₂	$λ^{2} E_{1} D_{1} H_{2}$	$- λ (E_{1} D_{1} + H_{2})$
F₃	$λ^{2} E_{1} D_{2} H_{1}$	$- λ (E_{1} H_{1} + D_{2})$
F₄	$λ^{2} E_{1} I_{1} I_{2}$	$λ (E_{1} I_{1} + I_{2})$
F₅	$\begin{array}{l} x^{} y^{} (1 - x^{}) (1 - y^{}) \cdot \\ (J_{11}^{'} \|_{x = x^{}} J_{22}^{'} \|_{y = y^{}} - \\ J_{12} \|_{y = y^{}} J_{21} \|_{x = x^{}}) \end{array}$	$\begin{array}{l} x^{} (1 - x^{}) J_{22}^{'} \|_{y = y^{}} + \\ y^{} (1 - y^{}) J_{11}^{'} \|_{x = x^{}} \end{array}$

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变量		含义	说明
	x	支持者选择转发信息的概率	0≤x≤1
支持者	T₁	支持者的信誉值	T ₁＞0
	K₁	支持者传播信息的基础收益	K ₁＞0
	C₁	支持者争议基金	C ₁＞0
	y	反对者选择举报信息的概率	0≤y≤1
反对者	T₂	反对者的信誉值	T ₂＞0
	K₂	反对者反馈信息的基础收益	K ₂＞0
	C₂	反对者争议基金	C ₂＞0

变量	含义	说明
α	收益状态下风险敏感度	0＜α＜1
β	亏损状态下风险敏感度	0＜β 1＜
λ	损失规避程度	λ＞ 1
γ	收益状态下决策函数的弯曲程度	0≤γ≤1
δ	亏损状态下决策函数的弯曲程度	0≤δ≤1

变量	含义	说明
μ₁	从众效应权重	0≤μ ₁≤1
P_{B 1}	信息转发热度	0≤P_B1≤1

约束条件编号	约束条件内容	从众	情景	沉默点	举报点	转发点	冲突点	中心点
一	D ₁＞0，I₁＞0	E ₁＞0	1		√	√
	D ₂＞0，I₂＞0	E ₁＜0	2					√
二	D ₁＞0，I₁＞0	E ₁＞0	3		√
	D ₂＜0，I₂＞0	E ₁＜0	4					√
三	D ₁＞0，I₁＞0	E ₁＞0	5		√
	D ₂＜0，I₂＜0	E ₁＜0	6				√
四	D ₁＜0，I₁＞0	E ₁＞0	7			√
	D ₂＞0，I₂＞0	E ₁＜0	8		√
五	D ₁＜0，I₁＞0	E ₁＞0	9					√
	D ₂＜0，I₂＞0	E ₁＜0	10		√
六	D ₁＜0，I₁＞0	E ₁＞0	11					√
	D ₂＜0，I₂＜0	E ₁＜0	12		√		√
七	D ₁＜0，I₁＜0	E ₁＞0	13			√
	D ₂＞0，I₂＞0	E ₁＜0	14		√
八	D ₁＜0，I₁＜0	E ₁＞0	15					√
	D ₂＜0，I₂＞0	E ₁＜0	16		√
九	D ₁＜0，I₁＜0	E ₁＞0	17				√
	D ₂＜0，I₂＜0	E ₁＜0	18		√

Evolutionary game model of information management mechanism for public opinion governance

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