Fake News Detection using Machine Learning

Abstract

Fake news on social media and various other media spreads and causes serious concern as it can cause a lot of social and national damage with devastating consequences. A lot of research has already focused on discovering it. In this white paper, we analyze research related to fake news detection and examine traditional machine learning models to classify fake news as true or false. Select
the best model to model your product using supervised machine learning algorithms that can Using tools such as Python Scikit-Learn, NLP for text analysis. This process leads to feature extraction and vectorization. We recommend using the Python library scikit-learn to
perform text data tokenization and feature extraction. This library contains useful tools such as count vectorizers. Then run and experiment with feature selection methods to select the best features to achieve the highest accuracy.