Detecting East Asian Prejudice on Social Media

The outbreak of COVID-19 has transformed societies across the world as governments tackle the health, economic and social costs of the pandemic. It has also raised concerns about the spread of hateful language and prejudice online, especially hostility directed against East Asia. In this paper we report on the creation of a classifier that detects and categorizes social media posts from Twitter into four classes: Hostility against East Asia, Criticism of East Asia, Meta-discussions of East Asian prejudice and a neutral class. The classifier achieves an F1 score of 0.83 across all four classes. We provide our final model (coded in Python), as well as a new 20,000 tweet training dataset used to make the classifier, two analyses of hashtags associated with East Asian prejudice and the annotation codebook. The classifier can be implemented by other researchers, assisting with both online content moderation processes and further research into the dynamics, prevalence and impact of East Asian prejudice online during this global pandemic.

[1]  Leon Derczynski,et al.  Directions in Abusive Language Training Data: Garbage In, Garbage Out , 2020, ArXiv.

[2]  Ona de Gibert,et al.  Hate Speech Dataset from a White Supremacy Forum , 2018, ALW.

[3]  Autumn Toney,et al.  Pro-Russian Biases in Anti-Chinese Tweets about the Novel Coronavirus , 2020, ArXiv.

[4]  Michael Wiegand,et al.  A Survey on Hate Speech Detection using Natural Language Processing , 2017, SocialNLP@EACL.

[5]  Ingmar Weber,et al.  Understanding Abuse: A Typology of Abusive Language Detection Subtasks , 2017, ALW@ACL.

[6]  F. Billé Sinophobia: Anxiety, Violence, and the Making of Mongolian Identity , 2014 .

[7]  Mauro Conti,et al.  All You Need is "Love": Evading Hate Speech Detection , 2018, ArXiv.

[8]  Frank Hutter,et al.  Decoupled Weight Decay Regularization , 2017, ICLR.

[9]  Matteo Cinelli,et al.  The COVID-19 social media infodemic , 2020, Scientific reports.

[10]  Ankur Taly,et al.  Counterfactual Fairness in Text Classification through Robustness , 2018, AIES.

[11]  Jeremy Blackburn,et al.  "Go eat a bat, Chang!": An Early Look on the Emergence of Sinophobic Behavior on Web Communities in the Face of COVID-19 , 2020, ArXiv.

[12]  N. F. Johnson,et al.  Hate multiverse spreads malicious COVID-19 content online beyond individual platform control , 2020, 2004.00673.

[13]  Marcus Tomalin,et al.  Quarantining online hate speech: technical and ethical perspectives , 2019, Ethics and Information Technology.

[14]  Ingmar Weber,et al.  Racial Bias in Hate Speech and Abusive Language Detection Datasets , 2019, Proceedings of the Third Workshop on Abusive Language Online.

[15]  Marco Guerini,et al.  CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech , 2019, ACL.

[16]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[17]  Omer Levy,et al.  BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension , 2019, ACL.

[18]  Anne Weber,et al.  Manual on Hate Speech , 2009 .

[19]  A. Strauss,et al.  Grounded theory , 2017 .

[20]  Dirk Hovy,et al.  Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter , 2016, NAACL.

[21]  Yejin Choi,et al.  The Risk of Racial Bias in Hate Speech Detection , 2019, ACL.

[22]  Omer Levy,et al.  RoBERTa: A Robustly Optimized BERT Pretraining Approach , 2019, ArXiv.

[23]  Thomas Wolf,et al.  DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter , 2019, ArXiv.

[24]  Scott A. Hale,et al.  Challenges and frontiers in abusive content detection , 2019, Proceedings of the Third Workshop on Abusive Language Online.

[25]  Susan Benesch,et al.  Dangerous speech and dangerous ideology: an integrated model for monitoring and prevention , 2016 .

[26]  Sandeep Soni,et al.  Racism is a Virus: Anti-Asian Hate and Counterhate in Social Media during the COVID-19 Crisis , 2020, ArXiv.

[27]  Ingmar Weber,et al.  Automated Hate Speech Detection and the Problem of Offensive Language , 2017, ICWSM.

[28]  Yiming Yang,et al.  XLNet: Generalized Autoregressive Pretraining for Language Understanding , 2019, NeurIPS.

[29]  I. Law,et al.  Hidden from public view? Racism against the UK's Chinese population , 2009 .

[30]  Andreas Musolff,et al.  Dehumanizing metaphors in UK immigrant debates in press and online media , 2015 .

[31]  J. Crowcroft,et al.  Leveraging Data Science to Combat COVID-19: A Comprehensive Review , 2020, IEEE Transactions on Artificial Intelligence.

[32]  Kevin Gimpel,et al.  ALBERT: A Lite BERT for Self-supervised Learning of Language Representations , 2019, ICLR.

[33]  John Costello All you need is love? , 2016, International journal of palliative nursing.

[34]  R. Imhoff,et al.  Differentiating Islamophobia: Introducing a New Scale to Measure Islamoprejudice and Secular Islam Critique , 2012 .

[35]  Ming-Wei Chang,et al.  BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.