The Impact of Individual Behaviors and Governmental Guidance Measures on Pandemic-Triggered Public Sentiment: Based on System Dynamics and Cross-Validation

The Impact of Individual Behaviors and Governmental Guidance Measures on Pandemic-Triggered Public Sentiment: Based on System Dynamics and Cross-Validation

Hainan Huang, Weifan Chen, Tian Xie, Yaoyao Wei, Ziqing Feng, Weijiong Wu

Negative online public sentiment generated by government mishandling of pandemics and other disasters can easily trigger widespread panic and distrust, causing great harm. It is important to understand the law of public sentiment dissemination and use it in a timely and appropriate way. Using the big data of online public sentiment during the COVID-19 period, this paper analyzes and establishes a cross-validation based public sentiment system dynamics model which can simulate the evolution processes of public sentiment under the effects of individual behaviors and governmental guidance measures. A concrete case of a violation of relevant regulations during COVID-19 epidemic that sparked public sentiment in China is introduced as a study sample to test the effectiveness of the proposed method. By running the model, the results show that an increase in government responsiveness contributes to the spread of positive social sentiment but also promotes negative sentiment. Positive individual behavior suppresses negative emotions while promoting the spread of positive emotions. Changes in the disaster context (epidemic) have an impact on the spread of sentiment, but the effect is mediocre.

2021

Pandemic, Cross validation, System Dynamics, public sentiment, simulation and control

10.3390/ijerph18084245

Epidemiology and Health

Korean Society of Epidemiology

Medicine