A Machine Learning Approach to Detect Fake News

Abstract

The project comes up with the applications of Machine Learning Technique to generate optimal model which is used to detect the fake news, spreading day by day in our life . Due to its potential to have major negative social, national, and international repercussions, fake news on social media and other media is pervasive and of serious concern. There has been a lot of study done already to try to find it.

In order to choose the optimum machine learning model, this study analyses the research on the identification of fake news.

In this machine learning model we Use the Python Scikit-Learn package to tokenize and extract features from text data because it has helpful tools like the count vectorizer and tiff vectorizer. In order to create a model of a product with the supervised machine learning algorithm where some data will be train and then after their training some sub-data will be tested for the required result, whether it is true or false. Our machine learning model will very appropriate to test the given news input