Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Various 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.

Objective

This study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19.

Methods

We 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.

Results

Our 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).

Conclusions

Our 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.

Related collections

Most cited references 30

Record: found
Abstract: not found
Article: not found

The Measurement of Observer Agreement for Categorical Data

J Landis, Gary G. Koch (1977)

0 comments Cited 6762 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Public perceptions, anxiety, and behaviour change in relation to the swine flu outbreak: cross sectional telephone survey

G James Rubin, Richard Amlôt, Lisa Page … (2009)

Objective To assess whether perceptions of the swine flu outbreak predicted changes in behaviour among members of the public in England, Scotland, and Wales. Design Cross sectional telephone survey using random digit dialling. Setting Interviews by telephone between 8 and 12 May. Participants 997 adults aged 18 or more who had heard of swine flu and spoke English. Main outcome measures Recommended change in behaviour (increases in handwashing and surface cleaning or plans made with a “flu friend”) and avoidance behaviours (engaged in one or more of six behaviours such as avoiding large crowds or public transport). Results 37.8% of participants (n=377) reported performing any recommended behaviour change “over the past four days . . . because of swine flu.” 4.9% (n=49) had carried out any avoidance behaviour. Controlling for personal details and anxiety, recommended changes were associated with perceptions that swine flu is severe, that the risk of catching it is high risk, that the outbreak will continue for a long time, that the authorities can be trusted, that good information has been provided, that people can control their risk of catching swine flu, and that specific behaviours are effective in reducing the risk. Being uncertain about the outbreak and believing that the outbreak had been exaggerated were associated with a lower likelihood of change. The strongest predictor of behaviour change was ethnicity, with participants from ethnic minority groups being more likely to make recommended changes (odds ratio 3.2, 95% confidence interval 2.0 to 5.3) and carry out avoidance behaviours (4.1, 2.0 to 8.4). Conclusions The results support efforts to inform the public about specific actions that can reduce the risks from swine flu and to communicate about the government’s plans and resources. Tackling the perception that the outbreak has been “over-hyped” may be difficult but worthwhile. Additional research is required into differing reactions to the outbreak among ethnic groups.

0 comments Cited 295 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak

Cynthia Chew, Gunther Eysenbach (2010)

Background Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary “infoveillance” approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms “H1N1” versus “swine flu” over time; 2) conduct a content analysis of “tweets”; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool. Methodology/Principal Findings Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords “swine flu,” “swineflu,” and/or “H1N1.” using Infovigil, an infoveillance system. Tweets using “H1N1” increased from 8.8% to 40.5% (R 2 = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data. Conclusions This study illustrates the potential of using social media to conduct “infodemiology” studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.

0 comments Cited 245 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Yangyang Liu:

ORCID: https://orcid.org/0000-0002-3197-7311

School of EducationTianjin University135 Yaguan RoadTianjin, 300350China86 18118849345liuyangyang661@sina.com

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J Med Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: November 2020

Publication date (Electronic): 25 November 2020

Publication date PMC-release: 25 November 2020

Volume: 22

Issue: 11

Electronic Location Identifier: e21933

Affiliations

[1 ] School of Education Tianjin University Tianjin China

[2 ] School of Media and Communication Shanghai Jiaotong University Shanghai China

[3 ] College of Life Sciences and Bioengineering, School of Science Beijing Jiaotong University Beijing China

[4 ] Office of International Cooperation and Exchanges Nanjing University Nanjing China

Author notes

Corresponding Author: Yangyang Liu liuyangyang661@ 123456sina.com

Author information

Wei Dong https://orcid.org/0000-0002-7632-2386

Jinhu Tao https://orcid.org/0000-0003-4316-0795

Xiaolin Xia https://orcid.org/0000-0002-4821-6228

Lin Ye https://orcid.org/0000-0001-9368-7160

Hanli Xu https://orcid.org/0000-0002-2082-2197

Peiye Jiang https://orcid.org/0000-0002-6669-5488

Yangyang Liu https://orcid.org/0000-0002-3197-7311

Article

Publisher ID: v22i11e21933

DOI: 10.2196/21933

PMC ID: 7690969

PubMed ID: 33112757

SO-VID: 951fdad8-eb08-4922-bf4d-00aad5410b2e

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 29 June 2020

Date revision requested : 31 July 2020

Date revision received : 12 August 2020

Date accepted : 26 October 2020

Comments

Comment on this article

scite_

Cited by 16

See all cited by

Most referenced authors 583

See all reference authors

- Version 1

Submit your digital health research with an established publisher
- celebrating 25 years of open access