Publication Type : Conference Paper
Source : (2021) CEUR Workshop Proceedings, 3159, pp. 589-602.
Url : https://ceur-ws.org/Vol-3159/T3-1.pdf
Campus : Coimbatore
School : School of Artificial Intelligence, School of Artificial Intelligence - Coimbatore
Year : 2021
Abstract : We present the results of HASOC-Dravidian-CodeMix shared task1 held at FIRE 2021, a track on offen- sive language identification for Dravidian languages in Code-Mixed Text in this paper. This paper will detail the task, its organisation, and the submitted systems. The identification of offensive language was viewed as a classification task. For this, 16 teams participated in identifying offensive language from Tamil-English code mixed data, 11 teams for Malayalam-English code mixed data and 14 teams for Tamil data. The teams detected offensive language using various machine learning and deep learn- ing classification models. This paper has analysed those benchmark systems to find out how well they accommodate a code-mixed scenario in Dravidian languages, focusing on Tamil and Malayalam.
Cite this Research Publication : Chakravarthi, B.R., Kumaresan, P.K., Sakuntharaj, R., Madasamy, A.K., Thavareesan, S., Premjith, B., Sreelakshmi, K., Navaneethakrishnan, S.C., McCrae, J.P., Mandl, T., "Overview of the HASOC-DravidianCodeMix Shared Task on Offensive Language Detection in Tamil and Malayalam," (2021) CEUR Workshop Proceedings, 3159, pp. 589-602.