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Netizens' concerns during COVID-19: a topic evolution analysis of Chinese social media platforms

大流行 人气 2019年冠状病毒病(COVID-19) 社会化媒体 政府(语言学) 独创性 政治学 价值(数学) 控制(管理) 公共关系 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 中国 社会学 社会科学 医学 计算机科学 法学 管理 经济 定性研究 传染病(医学专业) 病理 哲学 机器学习 疾病 语言学
作者
Zhaohua Deng,Rongyang Ma,Manli Wu,Richard Evans
出处
期刊:Kybernetes [Emerald Publishing Limited]
卷期号:54 (2): 1109-1127 被引量:1
标识
DOI:10.1108/k-04-2023-0583
摘要

Purpose This study analyzes the evolution of topics related to COVID-19 on Chinese social media platforms with the aim of identifying changes in netizens' concerns during the different stages of the pandemic. Design/methodology/approach In total, 793,947 posts were collected from Zhihu, a Chinese Question and Answer website, and Dingxiangyuan, a Chinese online healthcare community, from 31 December, 2019, to 4 August, 2021. Topics were extracted during the prodromal and outbreak stages, and in the abatement–resurgence cycle. Findings Netizens' concerns varied in different stages. During the prodromal and outbreak stages, netizens showed greater concern about COVID-19 news, the impact of COVID-19 and the prevention and control of COVID-19. During the first round of the abatement and resurgence stage, netizens remained concerned about COVID-19 news and the prevention and control of the pandemic, however, less attention was paid to the impact of COVID-19. During later stages, popularity grew in topics concerning the impact of COVID-19, while netizens engaged more in discussions about international events and the raising of spirits to fight the global pandemic. Practical implications This study contributes to the practice by providing a way for the government and policy makers to retrospect the pandemic and thereby make a good preparation to take proper measures to communicate with citizens and address their demands in similar situations in the future. Originality/value This study contributes to the literature by applying an adapted version of Fink's (1986) crisis life cycle to create a five-stage evolution model to understand the repeated resurgence of COVID-19 in Mainland China.
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