Author(s)

Zongjing Liang ¹, Qiuling Li ¹, Zhijie Li ¹, Yun Kuang ²

Affiliation(s)

¹ School of Economics and Management, Guangxi Normal University, Guilin, Guangxi, 541001, China
² Library, Guilin Normal University, Guilin, Guangxi, 541199, China

Corresponding Author

Yun Kuang

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.

KEYWORDS

Internet Public Opinion, Major Infectious Disease Epidemic, Autoregressive Distributed Lag Model, Public Opinion Prediction

CITE THIS PAPER

Zongjing Liang, Qiuling Li, Zhijie Li, Yun Kuang, The Impact of the Spread of Major Infectious Diseases on Internet Public Opnion. Media and Communication Research (2025) Vol. 6: 75-81. DOI: http://dx.doi.org/10.23977/mediacr.2025.060312.

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