ArticleJournal of medical Internet research2020
Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.
- Implementing Public Health Strategies-The Need for Educational Initiatives: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Group cognitive space of online rumors in public health emergencies: a theoretical and empirical study.Frontiers in public health · 2026Article
- Reconsidering Trust and Information Engagement and Unpacking the Role of Emotion in Public Responses During the Early Stage of a Public Health Crisis in China: Web-Based Survey Study.Online journal of public health informatics · 2025Article
- How the General Public Navigates Health Misinformation on Social Media: Qualitative Study of Identification and Response Approaches.JMIR infodemiology · 2025Article
- Article
- Chinese Public Attitudes and Opinions on Health Policies During Public Health Emergencies: Sentiment and Topic Analysis.Journal of medical Internet research · 2024Article
- Persuasive Effects of Crisis Communication during Public Health Emergency Outbreaks in China.Behavioral sciences (Basel, Switzerland) · 2024Article
- Difference in Rumor Dissemination and Debunking Before and After the Relaxation of COVID-19 Prevention and Control Measures in China: Infodemiology Study.Journal of medical Internet research · 2024Article
- Online rumors during the COVID-19 pandemic: co-evolution of themes and emotions.Frontiers in public health · 2024Article
- Exploring rumor behavior during the COVID-19 pandemic through an information processing perspective: The moderating role of critical thinking.Computers in human behavior · 2023Article
- Hot Topic Recognition of Health Rumors Based on Anti-Rumor Articles on the WeChat Official Account Platform: Topic Modeling.Journal of medical Internet research · 2023Article
- Understanding the role of social media usage and health self-efficacy in the processing of COVID-19 rumors: A SOR perspective.Data and information management · 2023Article
- The softening of Chinese digital propaganda: Evidence from theFrontiers in psychology · 2023Article
- Modeling emotional contagion in the COVID-19 pandemic: a complex network approach.PeerJ. Computer science · 2023Article
- How can the collaborative participation of regulators, whistleblowers, and parties effectively promote rumor management in public health emergencies?Frontiers in public health · 2023Article
- A survey on the publicZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2022Article
- New Insights Into the Social Rumor Characteristics During the COVID-19 Pandemic in China.Frontiers in public health · 2022Article
- Assessing Mechanisms Underlying the Sharing of Official and Unofficial Information during a Pandemic.International journal of environmental research and public health · 2021Article
- The causes, impacts and countermeasures of COVID-19 "Infodemic": A systematic review using narrative synthesis.Information processing & management · 2021Article
- Echo Chamber Effect in Rumor Rebuttal Discussions About COVID-19 in China: Social Media Content and Network Analysis Study.Journal of medical Internet research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVarious online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people's physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the epidemic may help generate useful strategies for guiding public emotions and dispelling rumors.
objectiveThis study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19.
methodsWe used the web-crawling tool Scrapy to gather data published by People's Daily on Sina Weibo, a popular social media platform in China, after January 8, 2020. Netizens' comments under each Weibo post were collected. Nearly 1 million comments thus collected were divided into 5 categories: happiness, sadness, anger, fear, and neutral, based on the underlying emotional information identified and extracted from the comments by using a manual identification process. Data on rumors spread online were collected through Tencent's Jiaozhen platform. Time-lagged cross-correlation analyses were performed to examine the relationship between public emotions and rumors.
resultsOur results indicated that the angrier the public felt, the more rumors there would likely be (r=0.48, P<.001). Similar results were observed for the relationship between fear and rumors (r=0.51, P<.001) and between sadness and rumors (r=0.47, P<.001). Furthermore, we found a positive correlation between happiness and rumors, with happiness lagging the emergence of rumors by 1 day (r=0.56, P<.001). In addition, our data showed a significant positive correlation between fear and fearful rumors (r=0.34, P=.02).
conclusionsOur findings confirm that public emotions are related to the rumors spread online in the context of COVID-19 in China. Moreover, these findings provide several suggestions, such as the use of web-based monitoring methods, for relevant authorities and policy makers to guide public emotions and behavior during this public health emergency.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.