@文章{info:doi/10.2196/19301，作者=“Budhwani, Henna和孙若燕”，标题=“在推特上引用新型冠状病毒为‘中国病毒’制造COVID-19污名:社交媒体数据的定量分析”，期刊=“J Med Internet Res”，年=“2020”，月=“5”，日=“6”，卷=“22”，数=“5”，页=“e19301”，关键词=“COVID-19;冠状病毒;推特;污名;社交媒体;背景:污名是一种有害的结构性力量，使具有不良特征的群体成员贬值。由于污名是由社会创造和强化的——通过面对面和在线社交互动——将新型冠状病毒称为“中国病毒”或“中国病毒”有可能产生和延续污名。目的:本研究的目的是评估在2020年3月16日美国总统提到“中国病毒”和“中国病毒”这个词后，推特上的短语是否增加了流行率和频率。方法:使用Sysomos软件(Sysomos, Inc)，我们使用一个关键词列表从美国提取推文，这些关键词是“中国病毒”的衍生品。“我们将3月9日至3月15日(前期)发布的全国和州层面的推文与3月19日至3月25日(后期)发布的推文进行了比较。 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. ", issn="1438-8871", doi="10.2196/19301", url="//www.mybigtv.com/2020/5/e19301/", url="https://doi.org/10.2196/19301", url="http://www.ncbi.nlm.nih.gov/pubmed/32343669" }