Exploring Amharic Hate Speech Data Collection and Classification Approaches
Language Technology Group, Universität Hamburg, Germany, Abinew Ali Ayele, Seid Muhie Yimam, Language Technology Group, Universität Hamburg, Germany, Tadesse Destaw Belay, Chris Biemann, Language Technology Group, Universität Hamburg, Germany · 2023
In this paper, we present a study of efficient data selection and annotation strategies for Amharic hate speech.We also build various classification models and investigate the challenges of hate speech data selection, annotation, and classification for the Amharic language.From a total of over 18 million tweets in our Twitter corpus, 15.1k tweets are annotated by two independent native speakers, and a Cohen's kappa score of 0.48 is achieved.A third annotator, a curator, is also employed to decide on the final gold labels.We employ both classical machine learning and deep learning approaches, which include fine-tuning AmFLAIR and AmRoBERTa contextual embedding models.Among all the models, AmFLAIR achieves the best performance with an F1-score of 72%.We publicly release the annotation guidelines, keywords/lexicon entries, datasets, models, and associated scripts with a permissive license 1 .