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Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the "Chinese virus" on Twitter: Quantitative Analysis of Social Media Data.

作者信息

Budhwani Henna, Sun Ruoyan

机构信息

Department of Health Care Organization and Policy, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States.

出版信息

J Med Internet Res. 2020 May 6;22(5):e19301. doi: 10.2196/19301.


DOI:10.2196/19301
PMID:32343669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7205030/
Abstract

BACKGROUND: Stigma is the deleterious, structural force that devalues members of groups that hold undesirable characteristics. Since stigma is created and reinforced by society-through in-person and online social interactions-referencing the novel coronavirus as the "Chinese virus" or "China virus" has the potential to create and perpetuate stigma. OBJECTIVE: The aim of this study was to assess if there was an increase in the prevalence and frequency of the phrases "Chinese virus" and "China virus" on Twitter after the March 16, 2020, US presidential reference of this term. METHODS: Using the Sysomos software (Sysomos, Inc), we extracted tweets from the United States using a list of keywords that were derivatives of "Chinese virus." We compared tweets at the national and state levels posted between March 9 and March 15 (preperiod) with those posted between March 19 and March 25 (postperiod). We used Stata 16 (StataCorp) for quantitative analysis, and Python (Python Software Foundation) to plot a state-level heat map. RESULTS: A total of 16,535 "Chinese virus" or "China virus" tweets were identified in the preperiod, and 177,327 tweets were identified in the postperiod, illustrating a nearly ten-fold increase at the national level. All 50 states witnessed an increase in the number of tweets exclusively mentioning "Chinese virus" or "China virus" instead of coronavirus disease (COVID-19) or coronavirus. On average, 0.38 tweets referencing "Chinese virus" or "China virus" were posted per 10,000 people at the state level in the preperiod, and 4.08 of these stigmatizing tweets were posted in the postperiod, also indicating a ten-fold increase. The 5 states with the highest number of postperiod "Chinese virus" tweets were Pennsylvania (n=5249), New York (n=11,754), Florida (n=13,070), Texas (n=14,861), and California (n=19,442). Adjusting for population size, the 5 states with the highest prevalence of postperiod "Chinese virus" tweets were Arizona (5.85), New York (6.04), Florida (6.09), Nevada (7.72), and Wyoming (8.76). The 5 states with the largest increase in pre- to postperiod "Chinese virus" tweets were Kansas (n=697/58, 1202%), South Dakota (n=185/15, 1233%), Mississippi (n=749/54, 1387%), New Hampshire (n=582/41, 1420%), and Idaho (n=670/46, 1457%). CONCLUSIONS: The rise in tweets referencing "Chinese virus" or "China virus," along with the content of these tweets, indicate that knowledge translation may be occurring online and COVID-19 stigma is likely being perpetuated on Twitter.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db97/7205030/adfa35522b66/jmir_v22i5e19301_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db97/7205030/adfa35522b66/jmir_v22i5e19301_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db97/7205030/adfa35522b66/jmir_v22i5e19301_fig1.jpg

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本文引用的文献

[1]
Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter.

Cureus. 2020-3-13

[2]
Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.

J Med Internet Res. 2020-4-21

[3]
How Do We Balance Tensions Between COVID-19 Public Health Responses and Stigma Mitigation? Learning from HIV Research.

AIDS Behav. 2020-7

[4]
The Twitter pandemic: The critical role of Twitter in the dissemination of medical information and misinformation during the COVID-19 pandemic.

CJEM. 2020-7

[5]
Twitter sentiment classification for measuring public health concerns.

Soc Netw Anal Min. 2015

[6]
Mental illness and bipolar disorder on Twitter: implications for stigma and social support.

J Ment Health. 2019-11-7

[7]
Flu Outbreak Prediction Using Twitter Posts Classification and Linear Regression With Historical Centers for Disease Control and Prevention Reports: Prediction Framework Study.

JMIR Public Health Surveill. 2019-6-25

[8]
Perceived Stigma in Health Care Settings and the Physical and Mental Health of People of Color in the United States.

Health Equity. 2019-3-21

[9]
The Burden of Stigma on Health and Well-Being: A Taxonomy of Concealment, Course, Disruptiveness, Aesthetics, Origin, and Peril Across 93 Stigmas.

Pers Soc Psychol Bull. 2017-12-31

[10]
E-Cigarette Surveillance With Social Media Data: Social Bots, Emerging Topics, and Trends.

JMIR Public Health Surveill. 2017-12-20

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