Abstract

Abstract:The role of social media in our day to day life has increased rapidly in recentyears. It is now used not only for social interaction, but also as an importantplatform for exchanging information and news. Twitter, Facebook amicro-blogging service, connects millions of users around the world and allowsfor the real-time propagation of information and news . Fake news has become amajor problem in these social networks . Fake news has become a major problemin these social networks Fake news has vast impact in our modern society.Detecting Fake news is an important step. This work purposes the use of machinelearning techniques to detect Fake news ,using Support Vector Machine(SVM)algorithm. The normalization method is important step for cleansing databefore using the machine learning method to classify data. This model count thecredibility of content and user reputation .This method develops a method forautomating fake news detection on social media by learning to predict accuracyassessments in credibility-focused Twitter dataset.

Keywords:Twittersocial network; reputation; credibility; machine learning.