"Stop Asian Hate!" : Refining Detection of Anti-Asian Hate Speech During
the COVID-19 Pandemic
- URL: http://arxiv.org/abs/2112.02265v1
- Date: Sat, 4 Dec 2021 06:55:19 GMT
- Title: "Stop Asian Hate!" : Refining Detection of Anti-Asian Hate Speech During
the COVID-19 Pandemic
- Authors: Huy Nghiem, Fred Morstatter
- Abstract summary: COVID-19 pandemic has fueled a surge in anti-Asian xenophobia and prejudice.
We create and annotate a corpus of Twitter tweets using 2 experimental approaches to explore anti-Asian abusive and hate speech.
- Score: 2.5227595609842206
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: *Content warning: This work displays examples of explicit and strongly
offensive language. The COVID-19 pandemic has fueled a surge in anti-Asian
xenophobia and prejudice. Many have taken to social media to express these
negative sentiments, necessitating the development of reliable systems to
detect hate speech against this often under-represented demographic. In this
paper, we create and annotate a corpus of Twitter tweets using 2 experimental
approaches to explore anti-Asian abusive and hate speech at finer granularity.
Using the dataset with less biased annotation, we deploy multiple models and
also examine the applicability of other relevant corpora to accomplish these
multi-task classifications. In addition to demonstrating promising results, our
experiments offer insights into the nuances of cultural and logistical factors
in annotating hate speech for different demographics. Our analyses together aim
to contribute to the understanding of the area of hate speech detection,
particularly towards low-resource groups.
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