Text mining of the media coverage of major public health emergencies: a case study of COVID-19
10.19428/j.cnki.sjpm.2021.20343
- VernacularTitle:重大突发公共卫生事件中的舆情特征及演化分析：以新冠肺炎疫情为例
- Author:
Shi-yu XIE
1
;
Hao-ran JIANG
;
Xiao-guang YANG
Author Information
1. School of Public Health, Fudan University, Shanghai 200032, China
- Publication Type:Research Article
- Keywords:
COVID-19;
characteristics of public opinion;
public opinion evolution;
topic model
- From:
Shanghai Journal of Preventive Medicine
2021;33(3):203-
- CountryChina
- Language:Chinese
-
Abstract:
Objective Based on the text analysis of COVID-19 media report, text mining was used to probe the trend of major public health emergencies and response of the government and social subjects in China. Methods Using the topic model method, we focused on the quantity of news report, topic content, development trend, and emotional tendency, to present the characteristics of media report on China's public health emergency, and the response mechanism of the Chinese government and the whole society. Results The media report and news commentary of COVID-19 showed a consistent trend with the epidemic progress. The governmental response was the main target of media report, while social power, medical progress and other categories also attracted some attention. The development trend of different topics was characterized by continual or periodic variation due to their different attributes. Conclusion The topic model method comprehensively demonstrates the development and response process of the COVID-19 epidemic. The model may provide a new perspective to improve the national public emergency management system.
