How online public opinion evolves before and after policy adjustments in response to major public health emergencies
Zhendong Niu, Yunyun Gao, Xusheng Wu, Qingyuan Hu, Dehua Hu

TL;DR
This study examines how public opinion changes before and after adjustments to pandemic control policies in China, using data from online platforms.
Contribution
The study provides new insights into public sentiment and opinion evolution following policy changes during public health emergencies.
Findings
Public opinion intensity surged initially but declined rapidly after targeted measures were announced.
Long-term public sentiment remained largely positive despite short-term negative reactions.
Discussion topics shifted from community control to economic and daily-life concerns over time.
Abstract
In recent years, incidents of public opinion triggered by major public health emergencies have emerged endlessly. Existing studies have focused on public attitudes during the early stages of containment measures but lacked research on how public opinion evolves after those measures are relaxed. In late 2022, however, China optimized its COVID-19 control measures, providing a unique window for this study. To reveal public attitudes toward the adjustment of response measures for major public health emergencies and how these attitudes evolve over time, and to provide a reference for improving related policies and managing public opinion. We collected Baidu Index and Weibo post data related to “epidemic prevention and control” between October 11, 2022 and March 15, 2023. Guided by the “Public Opinion Life Cycle Theory,” we analyzed the evolution of public opinion intensity using the Baidu…
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Taxonomy
TopicsData-Driven Disease Surveillance · Influenza Virus Research Studies · Public Health Policies and Education
