The problem Fake News Detection Using Machine Learning solves

Fake news spread through social media has become a serious problem, having the potential to result in
mob violence, suicides etc. as a result of misinformation circulated on social media. We have tried to build a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously, using a dataset consisting of about 40000 articles comprising of fake as well as real news. The model was created using Natural Language Processing wherein a pipeline was created and a classifier (SVM) was trained using fake and real news. The trained model is deployed as service to users.