Multilingual Racial Hate Speech Detection Using Transfer Learning
Language Technology Group, Universität Hamburg, Germany, Abinew Ali Ayele, Skadi Dinter, Language Technology Group, Universität Hamburg, Germany, Seid Muhie Yimam, Language Technology Group, Universität Hamburg, Germany, Chris Biemann, Language Technology Group, Universität Hamburg, Germany · 2023
The rise of social media eases the spread of hateful content, especially racist content with severe consequences.In this paper, we analyze the tweets targeting the death of George Floyd in May 2020 as the event accelerated debates on racism globally.We focus on the tweets published in French for a period of one month since the death of Floyd.Using the Yandex Toloka platform, we annotate the tweets into categories as hate, offensive or normal.Tweets that are offensive or hateful are further annotated as racial or non-racial.We build French hate speech detection models based on the multilingual BERT and CamemBERT and apply transfer learning by fine-tuning the HateXplain model.We compare different approaches to resolve annotation ties and find that the detection model based on CamemBERT yields the best results in our experiments.