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Characterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study

Authors :
Zhang, Shuai
Pian, Wenjing
Ma, Feicheng
Ni, Zhenni
Liu, Yunmei
Source :
JMIR Public Health and Surveillance, Vol 7, Iss 2, p e26090 (2021)
Publication Year :
2021
Publisher :
JMIR Publications, 2021.

Abstract

BackgroundThe COVID-19 infodemic has been disseminating rapidly on social media and posing a significant threat to people’s health and governance systems. ObjectiveThis study aimed to investigate and analyze posts related to COVID-19 misinformation on major Chinese social media platforms in order to characterize the COVID-19 infodemic. MethodsWe collected posts related to COVID-19 misinformation published on major Chinese social media platforms from January 20 to May 28, 2020, by using PythonToolkit. We used content analysis to identify the quantity and source of prevalent posts and topic modeling to cluster themes related to the COVID-19 infodemic. Furthermore, we explored the quantity, sources, and theme characteristics of the COVID-19 infodemic over time. ResultsThe daily number of social media posts related to the COVID-19 infodemic was positively correlated with the daily number of newly confirmed (r=0.672, P

Details

Language :
English
ISSN :
23692960
Volume :
7
Issue :
2
Database :
Directory of Open Access Journals
Journal :
JMIR Public Health and Surveillance
Publication Type :
Academic Journal
Accession number :
edsdoj.1827651d7b642ed8205cbfc6a4d7d17
Document Type :
article
Full Text :
https://doi.org/10.2196/26090