Fake News Detection with BERT

In this paper, we propose a fake news detection model using a fine-tuned BERT (Bidirectional Encoder Representations from Transformers) model.

Fake news has become a prevalent issue in today’s society, with the ability to spread rapidly and cause harm through misinformation. In this paper, we propose a fake news detection model using a fine-tuned BERT (Bidirectional Encoder Repre- sentations from Transformers) model. BERT is a powerful language model that has been successful in a variety of natural language processing tasks. We fine-tune the BERT model on a dataset of real and fake news articles from Kaggle, and evaluate its performance on a holdout test set. Our results achieve an accuracy of 0.574 on the fake news detection task.

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Research Paper