NEWS AUTHENTICITY DETECTION USING MACHINE LEARNING ALGORITHMS WITH FEATURE EXTRACTION METHODS

In this fast-paced urban technology era, we forgot all about our traditionally used magazines and newspapers and go in search of online news platforms and do not know to what extent those platforms are realistic. Some fake news is spread without knowing the truth or falsehood. In this paper, we put forward a system for detecting news authenticity that uses machine learning algorithms with feature extraction methods. We use Term Frequency- Inverse Document Frequency (TF-IDF) vectorizer, Decision Tree Classifier, Logistic Regression, Gradient Boosting Classifier, Random Forest Classifier. And the experimented outcome shows the great accuracy and precision.