FakeNews

Fake News Classifier

Implement a model that can classify if a news article is fake or real.

Two models-

Naive Bayes model using TFIDF and CountVectorisation to detect grammatical and syntactic differences between fake and real news. Convolutional Neural Network to model the word ordering and contextual differences between fake and real news. DataSet- Around 8,000 articles with a combination of equal parts fake and real news. Compiled the dataset using articles from the Kaggle Fake news dataset (based on US 2016 elections data) and tried to crawl for related political news articles for the real set from the web.