Chakravarthi, B.R.Priyadharshini, R.Jose, N.Anand Kumar, M.Mandl, T.Kumaresan, P.K.Ponnusamy, R.LekshmiAmmal, R.L.Mccrae, J.P.Sherly, E.2026-02-062021Proceedings of the 1st Workshop on Speech and Language Technologies for Dravidian Languages, DravidianLangTech 2021 at 16th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2021, 2021, Vol., , p. 133-145https://doi.org/https://idr.nitk.ac.in/handle/123456789/30272Detecting offensive language in social media in local languages is critical for moderating user-generated content. Thus, the field of offensive language identification for under-resourced languages like Tamil, Malayalam and Kannada is of essential importance. As user-generated content is often code-mixed and not well studied for under-resourced languages, it is imperative to create resources and conduct benchmark studies to encourage research in under-resourced Dravidian languages. We created a shared task on offensive language detection in Dravidian languages. We summarize the dataset for this challenge which are openly available at https://competitions.codalab.org/competitions/27654, and present an overview of the methods and the results of the competing systems. ©2021 Association for Computational Linguistics