Fake News Detection in Dravidian Languages Using Transformer Models

Nowadays, fake news is spreading rapidly. Many resources are available for fake news detection in high-resource languages like English. Due to the lack of annotated data and corpora for low-resource languages, detecting fake news in low-resource languages is difficult. There is a need for a system for fake news detection in low-resource languages like Dravidian languages. In this research, we used Telugu, Kannada, Tamil, and Malayalam languages and tested with four transformer models: mBERT, XLM-RoBERTa, IndicBERT, and MuRIL. MuRIL gives the best accuracy in these models compared to the remaining models.