Deep learning solution for detecting fake news

Abstract

Spread of Fake news is a major challenge in this digital age where information is shared through various means like internet articles or social media. Since the proliferation of fake news is on the rise, the spread of misinformation is a major concern. Spreading of fake news has wide repercussions as it has a wider reach due to straightforward access and rapid dispersion. This paper proposes a Deep Learning approach along with Natural Language Processing Techniques as the solution for fake news detection. We used ISOT dataset to train and test our model with GloVe model for word embeddings and bidirectional Long Short-Term Memory (LSTM) as the neural network classifier to achieve an accuracy of 99.35%.