Fake News Detection using Machine Learning

This work helps us to detect the accuracy of the fake news using different classification techniques. Fake news is significantly affecting our social life, in fact in every field mainly in politics, education. In this work, we have presented the solution for Fake news problem by implementing fake news detection model by using different classification techniques. Fake News Detection becomes complicated when it comes to resources. Resources like datasets are limited. In this model, we have used classification techniques like Support Vector Machine(SVM), Naïve Bayes, Passive Aggressive Classifier. Output of our model using feature extraction techniques as Term Frequency-Inverted Document Frequency (TF-IDF) and Support Vector Machine (SVM) as classifier, has accuracy of 95.05%.