期刊
AMERICAN JOURNAL OF PUBLIC HEALTH
卷 112, 期 4, 页码 646-649出版社
AMER PUBLIC HEALTH ASSOC INC
DOI: 10.2105/AJPH.2021.306653
关键词
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资金
- Immunology, Inflammation and Infectious Diseases Initiative of the University of Utah
- Office of the Vice President for Research of the University of Utah
The study illustrates a significant spatiotemporal distribution of anti-Asian hate language on Twitter during the early phase of the COVID-19 pandemic. Geographical clusters of hate varied in size, duration, strength, and location, scattered across the contiguous United States.
Objectives. To illustrate the spatiotemporal distribution of geolocated tweets that contain anti-Asian hate language in the contiguous United States during the early phase of the COVID-19 pandemic. Methods. We used a data set of geolocated tweets that match with keywords reflecting COVID-19 and anti-Asian hate and identified geographical clusters using the space-time scan statistic with Bernoulli model. Results. Anti-Asian hate language surged between January and March 2020. We found clusters of hate across the contiguous United States. The strongest cluster consisted of a single county (Ross County, Ohio), where the proportion of hateful tweets was 312.13 times higher than for the rest of the country. Conclusions. Anti-Asian hate on Twitter exhibits a significantly clustered spatiotemporal distribution. Clusters vary in size, duration, strength, and location and are scattered across the entire contiguous United States. Public Health Implications. Our results can inform decision-makers in public health and safety for allocating resources for place-based preparedness and response for pandemic-induced racism as a public health threat. (Am J Public Health. 2022;112(4):646-649. https://doi.org/10.2105/ AJPH.2021.306653)
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