NEWS AUTHENTICITY DETECTION USING MACHINE LEARNING ALGORITHMS WITH FEATURE EXTRACTION METHODS

NEWS AUTHENTICITY DETECTION USING MACHINE LEARNING ALGORITHMS WITH FEATURE EXTRACTION METHODS

Farjana Farvin S,

Assistant Professor, Department of Computer Science and Engineering, Anjalai Ammal Mahalingam Engineering College, Thiruvarur, India, farzana@aamec.edu.in

Shafinathun Rafiya A,

Student, Department of Computer Science and Engineering, Anjalai Ammal Mahalingam Engineering College Thiruvarur, India, a.rafiya2k@gmail.com

Abstract--- 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.

Keywords--- Machine Learning, Decision Tree Classifier, Term Frequency- Inverse Document Frequency (TF-IDF), Logistic Regression, Gradient Boosting Classifier, Random Forest Classifier