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J Med Internet Res. 2020 Apr 26. doi: 10.2196/19301. [Epub ahead of print]
Referencing the novel coronavirus as the "Chinese virus" or "China virus" on Twitter: COVID-19 stigma.
Budhwani H1, Sun R1.
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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:
Our objective was to assess if there was an increase in the frequency of the phrases "Chinese virus" and "China virus" on Twitter, post- the March 16, 2020 United States presidential reference of this term.
METHODS:
Using the Sysomos software, 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 9th and March 15th (pre-period) with those posted between March 19th and March 25th (post-period). We used Stata 16 for quantitative analysis and Python to plot a state-level heat map.
RESULTS:
A total of 16,535 "Chinese virus" or "China virus" tweets were identified in the pre-period and 177,327 of these tweets were identified in the post-period, illustrating an increase of nearly ten times at the national level. All fifty states witnessed an increase in the number of tweets exclusively mentioning "Chinese virus" or "China virus" instead of COVID-19 or coronavirus. On average, 0.38 tweets referencing "Chinese virus" or "China virus" were posted per 10,000 population at the state level in the pre-period, and 4.08 of these stigmatizing tweets were posted in the post-period, also indicating a ten fold increase. The five states with highest number of post-period "Chinese virus" tweets were: Pennsylvania (5,249), New York (11,754), Florida (13,070), Texas (14,861), and California (19,442). Adjusting for population size, the five states with the highest prevalence of post-period "Chinese virus" tweets were: Arizona (5.85), New York (6.04), Florida (6.09), Nevada (7.72), and Wyoming (8.76). The five states with the largest increase in pre- to post-period "Chinese virus" tweets were: Kansas (1,202%), South Dakota (1,233%), Mississippi (1,387%), New Hampshire (1,420%), and Idaho (1,457%).
CONCLUSIONS:
The rise in tweets referencing "Chinese virus" or "China virus," along with the content of these tweets, indicate that 1) knowledge translation may be occurring online and that 2) COVID-19 stigma is likely being perpetuated on Twitter.
CLINICALTRIAL:
PMID:32343669DOI:10.2196/19301
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