Detection of Fake News in Distributed Environment

Data analytics is the present and the future of problem-solving in computing. With the increasing trends in Data and Processing power, Machine learning solutions are evolving to cater to the needs and challenges in both scientific and business worlds. In this work, the current solutions have been discussed, and the results of the practical experiments are shown with a glimpse into the future direction. The task of automatic identification of fake news is addressed. Fake news datasets are obtained through crowdsourcing and web covering celebrities. Due to the inherent relationship among publishers, news and social engagements during the news dissemination process on social media, the SVM classifier model has been implemented, the Multilayer Perceptron model for distributed environment is proposed and a performance comparison of two models is established.