IDENTIFY FAKE NEWS WITH MACHINE LEARNING

Author (s) : Mrs N.SAVITHA and Dr.J.LOURDU XAVIER

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Abstract :
Research into detecting fake news is still in its early stages, as it is a relatively new wonder at the premium raised by society. We used machine learning algorithms and used three classifications to distinguish evidence from fake news; Passive Aggressive, Naïve Bayes and Support Vector Machine. The basic classification is not completely correct in detecting fake news because the ordering strategies are not specific to fake news. By combining machine learning and text-based processing, we can identify fake news and create classifiers that can collect news data. Text characterization mainly focuses on extracting different text features and then combining these features for classification. A huge test here is the lack of an expert method to distinguish fakes from non-fakes, because the cases are not accessible. We used three different machine learning classifiers on two freely available datasets. A test study based on the current data set shows potentiating and improved performance.

Keywords : Machine learning, Fake news

Conference Date : 17/09/2021

Pages : 53

Paper ID : IESMDT51