Spatial Distribution of Hateful Tweets Against Asians and Asian Americans During the COVID-19 Pandemic, November 2019 to May 2020.
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...
| Published in: | American Journal of Public Health Vol. 112; no. 4; pp. 646 - 650 |
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| Main Authors: | , , , , , |
| Format: | Article |
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American Public Health Association
Apr2022
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=155913531&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 155913531 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00900036 APH jtl: American Journal of Public Health issn: 00900036 maglogo: N pubinfo: dt: Apr2022 vid: 112 iid: 4 pid: 44 pub: American Public Health Association artinfo: ui: 155913531 10.2105/ajph.2021.306653 ppf: 646 ppct: 4 formats: tig: atl: Spatial Distribution of Hateful Tweets Against Asians and Asian Americans During the COVID-19 Pandemic, November 2019 to May 2020. aug: au: Hohl, Alexander Choi, Moongi Yellow Horse, Aggie J. Medina, Richard M. Wan, Neng Wen, Ming su: Twitter (Web resource) Anti-Asian racism COVID-19 pandemic Racism Public health sug: subj: Anti-Asian racism COVID-19 pandemic Racism Public health Health and Welfare Funds Twitter (Web resource) ab: 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 pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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