Predicting anti-Asian hateful users on Twitter during COVID-19

We investigate predictors of anti-Asian hate among Twitter users throughout COVID-19. With the rise of xenophobia and polarization that has accompanied widespread social media usage in many nations, online hate has become a major social issue, attracting many researchers. Here, we apply natural lang...

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Main Authors: AN, Jisun, KWAK, Haewoon, LEE, Claire Seungeun, JUN, Bogang, AHN, Yong-Yeol
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Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/6787
https://ink.library.smu.edu.sg/context/sis_research/article/7790/viewcontent/2021.findings_emnlp.398.pdf
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spelling sg-smu-ink.sis_research-77902022-01-27T10:00:15Z Predicting anti-Asian hateful users on Twitter during COVID-19 AN, Jisun KWAK, Haewoon LEE, Claire Seungeun JUN, Bogang AHN, Yong-Yeol We investigate predictors of anti-Asian hate among Twitter users throughout COVID-19. With the rise of xenophobia and polarization that has accompanied widespread social media usage in many nations, online hate has become a major social issue, attracting many researchers. Here, we apply natural language processing techniques to characterize social media users who began to post anti-Asian hate messages during COVID-19. We compare two user groups—those who posted anti-Asian slurs and those who did not—with respect to a rich set of features measured with data prior to COVID-19 and show that it is possible to predict who later publicly posted anti-Asian slurs. Our analysis of predictive features underlines the potential impact of news media and information sources that report on online hate and calls for further investigation into the role of polarized communication networks and news media. 2021-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6787 info:doi/https://aclanthology.org/2021.findings-emnlp.398 https://ink.library.smu.edu.sg/context/sis_research/article/7790/viewcontent/2021.findings_emnlp.398.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University COVID-19 hate speech Artificial Intelligence and Robotics Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic COVID-19
hate speech
Artificial Intelligence and Robotics
Numerical Analysis and Scientific Computing
spellingShingle COVID-19
hate speech
Artificial Intelligence and Robotics
Numerical Analysis and Scientific Computing
AN, Jisun
KWAK, Haewoon
LEE, Claire Seungeun
JUN, Bogang
AHN, Yong-Yeol
Predicting anti-Asian hateful users on Twitter during COVID-19
description We investigate predictors of anti-Asian hate among Twitter users throughout COVID-19. With the rise of xenophobia and polarization that has accompanied widespread social media usage in many nations, online hate has become a major social issue, attracting many researchers. Here, we apply natural language processing techniques to characterize social media users who began to post anti-Asian hate messages during COVID-19. We compare two user groups—those who posted anti-Asian slurs and those who did not—with respect to a rich set of features measured with data prior to COVID-19 and show that it is possible to predict who later publicly posted anti-Asian slurs. Our analysis of predictive features underlines the potential impact of news media and information sources that report on online hate and calls for further investigation into the role of polarized communication networks and news media.
format text
author AN, Jisun
KWAK, Haewoon
LEE, Claire Seungeun
JUN, Bogang
AHN, Yong-Yeol
author_facet AN, Jisun
KWAK, Haewoon
LEE, Claire Seungeun
JUN, Bogang
AHN, Yong-Yeol
author_sort AN, Jisun
title Predicting anti-Asian hateful users on Twitter during COVID-19
title_short Predicting anti-Asian hateful users on Twitter during COVID-19
title_full Predicting anti-Asian hateful users on Twitter during COVID-19
title_fullStr Predicting anti-Asian hateful users on Twitter during COVID-19
title_full_unstemmed Predicting anti-Asian hateful users on Twitter during COVID-19
title_sort predicting anti-asian hateful users on twitter during covid-19
publisher Institutional Knowledge at Singapore Management University
publishDate 2021
url https://ink.library.smu.edu.sg/sis_research/6787
https://ink.library.smu.edu.sg/context/sis_research/article/7790/viewcontent/2021.findings_emnlp.398.pdf
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