Abstract:

Understanding the intrinsic mechanisms of public opinion on emerging infectious diseases (EID) can assist the government in formulating precise guidance strategies. There is a lack of research that analyzes personalized guidance strategies from the perspective of heterogeneous netizens and dynamic evolution of public opinion. This paper, integrating Wilson’s model of information behavior, personality traits, and other theories, analyzes the interaction preferences of heterogeneous netizens’ opinion by using the vector autoregression model, designs the interaction process of netizens based on the Deffuant model, and constructs and calibrates a computational experimental model of EID public opinion guidance based on heterogeneous agents. Then, it analyzes the evolution of EID public opinion and the guidance strategy based on risk perception, emotion and interpersonal influence, and proposes the personalized guidance strategies for heterogeneous netizens in the EID context. This paper enriches the research on precise guidance of public opinion, helps the government understand and master the development trend of public opinion for EID, and guides the government to formulate precise guidance strategies for public opinion characteristics of EID and heterogeneous netizens.

Key words:

network public opinion on emerging infectious diseases (EID), interaction preferences, heterogeneous netizens, personalized guidance strategies

摘要：

理解新发传染病（EID）网络舆情的内在机制，能够协助政府制定精准网络舆情引导策略。目前尚缺乏从网民的异质性以及网络舆情的动态演化视角分析EID情境下个性化引导策略的研究。整合Wilson信息行为的三要素模型、人格特质等理论，采用向量自回归模型分析异质性网民的观点交互偏好，基于优化Deffuant模型设计EID网络舆情中网民的观点交互过程，构建了基于异质性Agent的EID网络舆情引导的计算实验模型并对其进行了校验；进而分析EID网络舆情的演化以及基于风险感知、情绪与人际影响力的引导策略，提出了EID情境下针对异质性网民群体的个性化引导策略。研究丰富了网络舆情的精准引导研究，同时帮助政府理解和掌握EID网络舆情的发展态势，并指导政府针对EID网络舆情特点以及异质性网民群体制定精准引导策略。

关键词:

新发传染病网络舆情, 观点交互偏好, 异质性网民, 个性化引导策略