  With the fast growth of mobile computing and Web technologies, offensive
language has become more prevalent on social networking platforms. Since
offensive language identification in local languages is essential to moderate
the social media content, in this paper we work with three Dravidian languages,
namely Malayalam, Tamil, and Kannada, that are under-resourced. We present an
evaluation task at FIRE 2020- HASOC-DravidianCodeMix and DravidianLangTech at
EACL 2021, designed to provide a framework for comparing different approaches
to this problem. This paper describes the data creation, defines the task,
lists the participating systems, and discusses various methods.
