Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the "Chinese virus" on Twitter: Quantitative Analysis of Social Media Data
Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the "Chinese virus" on Twitter: Quantitative Analysis of Social Media Data
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DOI：
10.2196/19301
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发表时间：
2020-05-06
影响因子：
7.4
通讯作者：
Sun, Ruoyan
中科院分区：
文献类型：
--
作者：
Budhwani, Henna;Sun, Ruoyan
背景：耻辱是一种有害的结构性力量，它贬低具有不良特征的群体成员。由于污名是由社会通过面对面和在线社交互动创造和强化的，将新型冠状病毒称为“中国病毒”或“中国病毒”有可能创造和延续污名。目的：本研究的目的是评估在 2020 年 3 月 16 日美国总统提及该术语后，Twitter 上“中国病毒”和“中国病毒”一词的流行度和频率是否有所增加。方法：使用 Sysomos在软件（Sysomos, Inc）中，我们使用“中国病毒”衍生的关键字列表提取了来自美国的推文。我们将 3 月 9 日至 3 月 15 日（前期）与 3 月 19 日至 3 月 25 日（后期）期间发布的国家和州级推文进行了比较。我们使用Stata 16（StataCorp）进行定量分析，使用Python（Python Software Foundation）绘制国家级热图。结果：前期共识别出16,535条“中国病毒”或“中国病毒”推文，后期识别出177,327条推文，国家层面增加了近十倍。所有 50 个州的推文数量均有所增加，专门提到“中国病毒”或“中国病毒”，而不是冠状病毒疾病 (COVID-19) 或冠状病毒。平均而言，前期国家层面每万人发布的涉及“中国病毒”或“中国病毒”的推文数量为0.38条，后期发布的此类污名化推文数量为4.08条，也表明增长了10倍。后期“中国病毒”推文数量最多的 5 个州是宾夕法尼亚州（n=5249）、纽约州（n=11,754）、佛罗里达州（n=13,070）、德克萨斯州（n=14,861）和加利福尼亚州（n=19,442）。调整人口规模后，“中国病毒”推文流行率最高的 5 个州是亚利桑那州（5.85）、纽约州（6.04）、佛罗里达州（6.09）、内华达州（7.72）和怀俄明州（8.76）。前后“中国病毒”推文增幅最大的 5 个州是堪萨斯州 (n=697/58, 1202%)、南达科他州 (n=185/15, 1233%)、密西西比州 (n=749/54, 1387%)、新罕布什尔州 (n=582/41, 1420%) 和爱达荷州(n=670/46, 1457%)。结论：提及“中国病毒”或“中国病毒”的推文数量的增加以及这些推文的内容表明，知识翻译可能正在网上发生，并且 COVID-19 的耻辱可能会在 Twitter 上长期存在。
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.