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ORIGINAL RESEARCH article
Front. Public Health
Sec. Digital Public Health
Volume 12 - 2024 |
doi: 10.3389/fpubh.2024.1489006
This article is part of the Research Topic Extracting Insights from Digital Public Health Data using Artificial Intelligence, Volume III View all 7 articles
The emotions of Chinese netizens toward the opening-up policies for COVID-19: panic, trust, and acceptance
Provisionally accepted- Guangxi University, Nanning, China
With the development of social media platforms such as Weibo, they have provided a broad platform for the expression of public sentiments during the pandemic.This study aims to explore the emotional attitudes of Chinese netizens toward the COVID-19 opening-up policies and their related thematic characteristics. Using Python, 145,851 texts were collected from the Weibo platform. Sentiment analysis and topic modeling techniques were employed to reveal the distribution of public emotions and key themes. The study found that the proportions of emotions were as follows: Good (46%), Happy (11%), Anger (17%), Disgust (6%), Sadness (10%), Surprise (2%), and Fear (8%). Through topic analysis, the following main themes were identified: medical resource shortages, healthcare workers, national policies, and COVID-19 sequelae.Based on the results of sentiment and topic analysis, public emotions toward the COVID-19 opening-up policies were categorized into three dimensions: panic, trust, and acceptance. Panic was primarily associated with medical resource shortages, concerns about COVID-19 sequelae, and doubts about policy transparency and fairness.Trust was reflected in public gratitude toward healthcare workers and support for national policies. Acceptance represented the public's optimism about returning to normal life. The findings demonstrate that changes in public emotions not only reflect the social impact of policy implementation but also highlight the critical roles of medical resource allocation, information transparency, and psychological health support in adjusting pandemic policies. This study provides empirical evidence and theoretical support for the government to develop more precise pandemic control strategies.
Keywords: Sina Weibo, Topic Modeling, COVID-19, opening-up policies, public emotions
Received: 31 Aug 2024; Accepted: 20 Dec 2024.
Copyright: © 2024 Dang and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Qiong Dang, Guangxi University, Nanning, China
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