Year: 2025
Type: article
Abstract: This paper uses the autoregressive distributed lag model (i.e., ARDL model) to study the impact of the COVID-19 pandemic on changes in online public opinion. The research objects of this paper are four types of online public opinion platforms (Weibo, short videos, electronic newspapers or magazines, and online news) and the number of new COVID-19 infections per day during the same period. The research method is the autoregressive distributed lag model (i.e., ARDL model). Research conclusions: (1) There is a long-term equilibrium relationship between the epidemic and public opinion. (2) Public opinion prediction is achieved based on the epidemic, and the prediction accuracy is high. (3) Cross-platform performance comparison of public opinion is achieved. This study can achieve innovations in the theory and practice of public opinion dissemination. The research conclusions can provide real-time public opinion reference materials for the prevention and control of major infectious diseases that may occur again in the future.
Source: Media and Communication Research
Authors: Zongjing Liang, Qiuling Li, Zhijie Li, Yun Kuang
Institution: Guangxi Normal University
Language: English
Subfield: Communication
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Award: G5550031169
OpenAlex ID: W4411736893