Machine Learning Techniques for the Classification of Fake News

Social Networking sites like Twitter, Instagram, and Facebook have become an essential part of our daily lives, but social media comes with its own advantages and disadvantages. Many of the time, these social networking platforms are used to distribute fake news or incorrect information, and there is a growing demand for classification and categorization of this type of content. As a result, we have explored a novel technique for classifying fake news that incorporates machine learning methods. This paper describes the development of a method that provides the TF-IDF Vectorizer to classify which news is legitimate and which is fraudulent. Implementation is performed using datasets from Kaggle. The results indicate that this method performs effectively.