SSNCSE NLP@TamilNLP-ACL2022: Transformer based approach for detection of abusive comment for Tamil language
B. Bharathi, Josephine Varsha · 2022
Social media platforms along with many other public forums on the Internet have shown a significant rise in the cases of abusive behavior such as Misogynism, Misandry, Homophobia, and Cyberbullying.To tackle these concerns, technologies are being developed and applied, as it is a tedious and time-consuming task to identify, report and block these offenders.Our task was to automate the process of identifying abusive comments and classify them into appropriate categories.The datasets provided by the DravidianLangTech@ACL2022 organizers were a code-mixed form of Tamil text.We trained the datasets using pre-trained transformer models such as BERT,m-BERT, and XLNET and achieved a weighted average of F1 scores of 0.96 for Tamil-English code mixed text and 0.59 for Tamil text.