Deep Learning Models for Multilingual Hate Speech Detection

Abstract

Hate speech detection is a challenging problem with most of the datasets available in only one language: English. In this paper, we conduct a large scale analysis of multilingual hate speech in 9 languages from 16 different sources. We observe that in low resource setting, simple models such as LASER embedding with logistic regression performs the best, while in high resource setting BERT based models perform better. In case of zero-shot classification, languages such as Italian and Portuguese achieve good results. Our

Publication
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery, 2020

Main contributions

Coming soon

Limitations

Coming soon

Future Directions

Coming soon

Related