Automatic Fake News Detection in Urdu Language using Transformers

Due to easy access to the internet, the content on social media increased drastically. It is easy to write or spread anything on the web without taking care of the trustfulness of the source. Fake news is now a whole society’s problem, sometimes fakes news spread faster than real news. It has adverse effects on people and firms. This makes automatic fake news detection an essential task. Automatic fake news detection has been using in different domains, including social media posts, health, and well-being news, political news, etc. This paper presents the Instituto Politécnico Nacional (Mexico) at FIRE 2021¹ for Urdu language fake news detection shared task [1, 2]. This paper aims to detect fake news on Urdu fake news articles belongs to six different domains, i.e., business, health, showbiz, sports, and technology. In the proposed approach, we applied the state-of-the-art transfer learning algorithm BERT. The best result of 0.91 (see Table 3) is obtained when we trained and validated our model before predictions on the test set. We submitted two different runs of the BERT model in this shared task. Our systems achieved 0.66 accuracy on the unlabeled test dataset provided to evaluate the submitted systems.