Fake News Detection Using Ensemble Technique in Machine Learning.
This fake news detection research paper represents use of ensemble learning model for detecting fake news, that means misleading information comes from non-reputable or unwanted resources. Information which is present on Internet, specifically on isocial imedia ilike iFacebook, itwitter, ietc... those are increasingly factors related to fake news. In this research paper we used various ensemble learning techniques for detecting fake news and apply those techniques on online news. These methods use ensemble techniques such as Boosting Technique, Bagging Technique and Stacking Technique to predict whether online news will be fake or real. And we used several ensemble techniques to improve accuracy of our dataset. And this result describes, that is the ifake inews idetection iproblem related with imachine ilearning imethods. In this paper, we demonstrate use of Ensemble Technique. We use fake news datasets, which is textual dataset. Therefore, this study aims at examining the different algorithms and evaluates the efficiency of the algorithms using different performance measures, i.e. accuracy. Keywords - Ensemble Learning, Fake News, Bagging Technique, Boosting Technique and Stacking Technique.