{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/offensive-language-detection-in-under","title":"Offensive Language Detection in Under-resourced Algerian Dialectal Arabic Language","arxiv_id":"2203.10024","date":"2022-03-18","proceeding":null,"authors":["Oussama Boucherit","Kheireddine Abainia"],"abstract":"This paper addresses the problem of detecting the offensive and abusive content in Facebook comments, where we focus on the Algerian dialectal Arabic which is one of under-resourced languages. The latter has a variety of dialects mixed with different languages (i.e. Berber, French and English). In addition, we deal with texts written in both Arabic and Roman scripts (i.e. Arabizi). Due to the scarcity of works on the same language, we have built a new corpus regrouping more than 8.7k texts manually annotated as normal, abusive and offensive. We have conducted a series of experiments using the state-of-the-art classifiers of text categorisation, namely: BiLSTM, CNN, FastText, SVM and NB. The results showed acceptable performances, but the problem requires further investigation on linguistic features to increase the identification accuracy.","url_abs":"https://arxiv.org/abs/2203.10024v1","url_pdf":"https://arxiv.org/pdf/2203.10024v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"offensive-language-detection-in-under","repo_url":"https://github.com/xprogramer/dziriofn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":"bilstm","method_name":"BiLSTM"},{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"svm","method_name":"SVM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}