Fake News Detection using Naive Bayes Classifier and Passive Aggressive Classifier

The rapid growth of fake news, as well as its damaging effects on every area of our lives, has increased the demand for detecting and combating fake news. As a result, distinguishing between real and fake news is critical. However, due to the massive amount of information generated every minute on the Internet, making this distinction manually is extremely difficult. This study will suggest an approach for detecting fake news and a mechanism for implementing it on social media. In this paper, the Naive Bayes Classifier and Passive Aggressive Classifier techniques will be used to detect fake news. The results will prove that the problem of identifying fake news is possible if Machine learning and Natural Language Processing algorithm are used.