Name: Corpus of Offensive Language in Arabic
Description: a dataset of YouTube comments in Arabic, specifically designed to be used for thedetection of offensive language in a machine learning scenario
Provider: University of Limerick
Paper Title: Dataset Construction for the Detection of Anti-Social Behaviour in
  Online Communication in Arabic
Tasks: offensive language detection, hate speech detection
Venue Name: nternational Conference on AI in Computational Linguistics
Authors: Azalden Alakrot,Liam Murray,Nikola S. Nikolov
Abstract: Abstract Warning: this paper contains a range of words which may cause offence. In recent years, many studies target anti-social behaviour such as offensive language and cyberbullying in online communication. Typically, these studies collect data from various reachable sources, the majority of the datasets being in English. However, to the best of our knowledge, there is no dataset collected from the YouTube platform targeting Arabic text and overall there are only a few datasets of Arabic text, collected from other social platforms for the purpose of offensive language detection. Therefore, in this paper we contribute to this field by presenting a dataset of YouTube comments in Arabic, specifically designed to be used for the detection of offensive language in a machine learning scenario. Our dataset contains a range of offensive language and flaming in the form of YouTube comments. We document the labelling process we have conducted, taking into account the difference in the Arab dialects and the diversity of perception of offensive language throughout the Arab world. Furthermore, statistical analysis of the dataset is presented, in order to make it ready for use as a training dataset for predictive modelling.