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Shifting sentiments: analyzing public reaction to COVID-19 containment policies in Wuhan and Shanghai through Weibo data

Sociology

Shifting sentiments: analyzing public reaction to COVID-19 containment policies in Wuhan and Shanghai through Weibo data

Z. Liu, J. Wu, et al.

Discover the intricate relationship between China's COVID-19 containment policies and public sentiment in this compelling study. By analyzing Weibo data, researchers Zhihang Liu, Jinlin Wu, Connor Y. H. Wu, and Xinming Xia uncover how public sentiment shifted from initial support to rising dissatisfaction amid lockdowns in Wuhan and Shanghai. This research sheds light on pandemic fatigue and its socio-economic implications, offering crucial insights for policymakers.

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Playback language: English
Abstract
This study examines the dynamic relationship between China's COVID-19 containment policies and public sentiment, focusing on the lockdowns in Wuhan and Shanghai. Using natural language processing (NLP) on Weibo data, the study reveals a shift in public sentiment from initial support to growing dissatisfaction, highlighting the impact of 'pandemic fatigue' and socio-economic factors. The research offers insights into the spatial variations of sentiment across different demographic and socio-economic groups, providing valuable lessons for policymakers in mitigating negative public perceptions and fostering compliance during health crises.
Publisher
Humanities and Social Sciences Communications
Published On
Aug 29, 2024
Authors
Zhihang Liu, Jinlin Wu, Connor Y. H. Wu, Xinming Xia
Tags
COVID-19
public sentiment
Wuhan lockdown
Shanghai lockdown
pandemic fatigue
natural language processing
socio-economic factors

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