FAKE NEWS DETECTION USING MACHINE LEARNING TECHNIQUES
Hyndavi Tumati, Shalem Raju Yadala, Navyasri Indupalli, Suneetha Manne · Journal of Critical Reviews · 2020
Information preciseness on Internet, especially on social media, is an more and more vital concern, but web-scale data hampers, potential to identify, consider and correct such data, or so referred to as fake news present in these systems in the present literature. There exists a giant physique of lookup on the subject matter of computer gaining knowledge of methods for deception detection, most of it has been focusing on classifying online opinions and publicly on hand social media posts and there are many algorithms used for fake information detection, and present authors cannot use benchmark dataset for this detection respectively. In this mini project, we will a suggest a approach for pretend information detection and ways to follow it on LIAR data set, it is a benchmark records set. This approach uses different computing device learning classification models to predict whether the information will be labelled as REAL or FAKE.