Latent Hatred: A Benchmark for Understanding Implicit Hate Speech

Mai ElSherief, Caleb Ziems, David Muchlinski, Vaishnavi Anupindi, Jordyn Seybolt, Munmun De Choudhury, Diyi Yang


Abstract
Hate speech has grown significantly on social media, causing serious consequences for victims of all demographics. Despite much attention being paid to characterize and detect discriminatory speech, most work has focused on explicit or overt hate speech, failing to address a more pervasive form based on coded or indirect language. To fill this gap, this work introduces a theoretically-justified taxonomy of implicit hate speech and a benchmark corpus with fine-grained labels for each message and its implication. We present systematic analyses of our dataset using contemporary baselines to detect and explain implicit hate speech, and we discuss key features that challenge existing models. This dataset will continue to serve as a useful benchmark for understanding this multifaceted issue.
Anthology ID:
2021.emnlp-main.29
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
345–363
Language:
URL:
https://aclanthology.org/2021.emnlp-main.29
DOI:
10.18653/v1/2021.emnlp-main.29
Bibkey:
Cite (ACL):
Mai ElSherief, Caleb Ziems, David Muchlinski, Vaishnavi Anupindi, Jordyn Seybolt, Munmun De Choudhury, and Diyi Yang. 2021. Latent Hatred: A Benchmark for Understanding Implicit Hate Speech. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 345–363, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Latent Hatred: A Benchmark for Understanding Implicit Hate Speech (ElSherief et al., EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.29.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.29.mp4
Code
 gt-salt/implicit-hate
Data
Implicit HateConceptNetHate SpeechWebText