COVID-19: A Pandemic of Anti-Asian Cyberhate
Hateful online attacks targeting individuals of Asian descent have increased dramatically in the wake of the coronavirus pandemic. This study examines daily trends in inflammatory keywords associated with anti-Asian cyberhate using data collected from Twitter between January 1, 2020 and February 28,...
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Gonzaga Library Publishing
2021
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oai:doaj.org-article:40ccdf860c4a4522a5522f8cabe4337d2021-11-08T08:10:53ZCOVID-19: A Pandemic of Anti-Asian Cyberhate2169-744210.33972/jhs.198https://doaj.org/article/40ccdf860c4a4522a5522f8cabe4337d2021-10-01T00:00:00Zhttps://jhs.press.gonzaga.edu/articles/198https://doaj.org/toc/2169-7442Hateful online attacks targeting individuals of Asian descent have increased dramatically in the wake of the coronavirus pandemic. This study examines daily trends in inflammatory keywords associated with anti-Asian cyberhate using data collected from Twitter between January 1, 2020 and February 28, 2021. Additionally, we explore the sentiment of tweets and track the evolution of discourse on Twitter regarding Asians and the coronavirus. Our results indicate that the usage of inflammatory keywords associated with anti-Asian hate on Twitter rose dramatically at the outset of the outbreak, and then spiked at various points over the next fourteen months. Notably, offline events and rhetoric appear to have affected the rate of hateful tweets about the pandemic targeting Asians. Additionally, we find that discourse on Twitter around the words 'China, Chinese, Asians', and 'virus' has become increasingly negative and stigmatizing during the course of the coronavirus outbreak.Matthew CostelloLong ChengFeng LuoHongxin HuSong LiaoNishant VishwamitraMingqi LiEbuka OkpalaGonzaga Library PublishingarticlePolitical science (General)JA1-92Social sciences (General)H1-99ENJournal of Hate Studies, Vol 17, Iss 1 (2021) |
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DOAJ |
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EN |
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Political science (General) JA1-92 Social sciences (General) H1-99 |
spellingShingle |
Political science (General) JA1-92 Social sciences (General) H1-99 Matthew Costello Long Cheng Feng Luo Hongxin Hu Song Liao Nishant Vishwamitra Mingqi Li Ebuka Okpala COVID-19: A Pandemic of Anti-Asian Cyberhate |
description |
Hateful online attacks targeting individuals of Asian descent have increased dramatically in the wake of the coronavirus pandemic. This study examines daily trends in inflammatory keywords associated with anti-Asian cyberhate using data collected from Twitter between January 1, 2020 and February 28, 2021. Additionally, we explore the sentiment of tweets and track the evolution of discourse on Twitter regarding Asians and the coronavirus. Our results indicate that the usage of inflammatory keywords associated with anti-Asian hate on Twitter rose dramatically at the outset of the outbreak, and then spiked at various points over the next fourteen months. Notably, offline events and rhetoric appear to have affected the rate of hateful tweets about the pandemic targeting Asians. Additionally, we find that discourse on Twitter around the words 'China, Chinese, Asians', and 'virus' has become increasingly negative and stigmatizing during the course of the coronavirus outbreak. |
format |
article |
author |
Matthew Costello Long Cheng Feng Luo Hongxin Hu Song Liao Nishant Vishwamitra Mingqi Li Ebuka Okpala |
author_facet |
Matthew Costello Long Cheng Feng Luo Hongxin Hu Song Liao Nishant Vishwamitra Mingqi Li Ebuka Okpala |
author_sort |
Matthew Costello |
title |
COVID-19: A Pandemic of Anti-Asian Cyberhate |
title_short |
COVID-19: A Pandemic of Anti-Asian Cyberhate |
title_full |
COVID-19: A Pandemic of Anti-Asian Cyberhate |
title_fullStr |
COVID-19: A Pandemic of Anti-Asian Cyberhate |
title_full_unstemmed |
COVID-19: A Pandemic of Anti-Asian Cyberhate |
title_sort |
covid-19: a pandemic of anti-asian cyberhate |
publisher |
Gonzaga Library Publishing |
publishDate |
2021 |
url |
https://doaj.org/article/40ccdf860c4a4522a5522f8cabe4337d |
work_keys_str_mv |
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