IRlab@IIT-BHU at SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media using SVM

Abstract

This paper describes the IRlab@IIT-BHU system for the OffensEval 2020. We take the SVM with TF-IDF features to identify and categorize hate speech and offensive language in social media for two languages. In subtask A, we used a linear SVM classifier to detect abusive content in tweets, achieving a macro F1 score of 0.779 and 0.718 for Arabic and Greek, respectively. © 2020 14th International Workshops on Semantic Evaluation, SemEval 2020 - co-located 28th International Conference on Computational Linguistics, COLING 2020, Proceedings. All rights reserved.