Abstract
While analysis of online explicit abusive language detection has lately seen an ever-increasing focus, implicit abuse detection remains a largely unexplored space. We carry out a study on a subcategory of implicit hate: euphemistic hate speech. We propose a method to assist in identifying unknown euphemisms (or code words) given a set of hateful tweets containing a known code word. Our approach leverages word embeddings and network analysis (through centrality measures and community detection) in a manner that can be generalized to identify euphemisms across contexts- not just hate speech.- Anthology ID:
- W18-5112
- Volume:
- Proceedings of the 2nd Workshop on Abusive Language Online (ALW2)
- Month:
- October
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Darja Fišer, Ruihong Huang, Vinodkumar Prabhakaran, Rob Voigt, Zeerak Waseem, Jacqueline Wernimont
- Venue:
- ALW
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 93–100
- Language:
- URL:
- https://aclanthology.org/W18-5112
- DOI:
- 10.18653/v1/W18-5112
- Cite (ACL):
- Rijul Magu and Jiebo Luo. 2018. Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks. In Proceedings of the 2nd Workshop on Abusive Language Online (ALW2), pages 93–100, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks (Magu & Luo, ALW 2018)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/W18-5112.pdf