COVID-19 related discrimination in Japan: A preliminary analysis utilizing text-mining. Issue 36 (10th September 2021)

• Record Type: Journal Article
• Authors: Suzuki, Reina; Iizuka, Yusuke; Lefor, Alan Kawarai
• Other Names: Eseadi. Chiedu section editor.
• Is Part Of: Medicine. Volume 100:Issue 36(2021)
• Publication Date: 2021-09-10
• Subjects: coronavirus disease of 2019 -- discrimination -- health care providers -- rural area -- text-mining; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000027105
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: To assess the general Japanese population's thoughts on coronavirus disease of 2019 related discrimination by Tweets. Tweets were retrieved from search queries using the keywords "health care providers and discrimination (no hashtags)" and "corona and rural area (no hashtags)" via the Twitter application programming interface. Subsequently, a text-mining analysis was conducted on tokenized text data. R version 4.0.2 was used for the analysis. In total, 51, 906 tweets for "corona and health care providers", 59, 560 tweets for "corona and rural" were obtained between the search period of July 29, 2020 and September 30, 2020. The most common 20 words from the tokenized text data were translated to English. Word clouds with the original Japanese words are presented. Tweets for corona and health care providers did not suggest significant evidence of discrimination toward health care providers on Twitter. Results for corona and rural area, however, showed the unexpected word "murahachibu" (an outmoded word meaning ostracism), suggesting persistent strong social pressure to prevent bringing the disease to the community. This kind of pressure may not be supported by scientific facts. These results demonstrate the need for continued educational efforts to disseminate factual information to the public.