A Survey on Hate Speech Detection using Natural Language Processing

Anna Schmidt, Michael Wiegand


Abstract
This paper presents a survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing. Due to the massive scale of the web, methods that automatically detect hate speech are required. Our survey describes key areas that have been explored to automatically recognize these types of utterances using natural language processing. We also discuss limits of those approaches.
Anthology ID:
W17-1101
Volume:
Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media
Month:
April
Year:
2017
Address:
Valencia, Spain
Editors:
Lun-Wei Ku, Cheng-Te Li
Venue:
SocialNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–10
Language:
URL:
https://aclanthology.org/W17-1101
DOI:
10.18653/v1/W17-1101
Bibkey:
Cite (ACL):
Anna Schmidt and Michael Wiegand. 2017. A Survey on Hate Speech Detection using Natural Language Processing. In Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media, pages 1–10, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
A Survey on Hate Speech Detection using Natural Language Processing (Schmidt & Wiegand, SocialNLP 2017)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp22-frontmatter/W17-1101.pdf