Hate Speech Detection and Reclaimed Language: Mitigating False Positives and Compounded Discrimination-Reference-Cited by-同舟云学术

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Hate Speech Detection and Reclaimed Language: Mitigating False Positives and Compounded Discrimination

Published:2024-05-21 Issue: Volume: Page:241-249
ISSN:
Container-title:ACM Web Science Conference
language:
Short-container-title:

Author:

Zsisku Eszter¹^ORCID,Zubiaga Arkaitz¹^ORCID,Dubossarsky Haim²^ORCID

Affiliation:

1. School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom

2. School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom and Language Technology Lab, University of Cambridge, United Kingdom

Funder

Riksbankens Jubileumsfond

Publisher

ACM

Reference28 articles.

1. Building for tomorrow: Assessing the temporal persistence of text classifiers

2. Pete Burnap and Matthew L Williams. 2015. Cyber hate speech on twitter: An application of machine classification and statistical modeling for policy and decision making. Policy & internet 7, 2 (2015), 223–242.

3. Automated Hate Speech Detection and the Problem of Offensive Language

4. Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior

5. Evidencing the harms of hate speech

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