Intelligent News Aggregator and Validator

In recent years, the widespread of fake news is growing at an alarming rate. So much so that it has turned into a social issue. So recognizing and distinguishing fake news is an important task which must be accomplished with proper ideas and science behind it. In this paper we are proposing a concept application, which will help users to discern fake news amongst all sort of news which is available on internet. The application will provide users with up to date news using simple news aggregator along with news validation, the news will be classified into 3 Categories fake, genuine and neutral. The validation will be performed in two stages; first using machine learning and second based on news rating provided by the users of news aggregator. The rating provided by the users will also be validating in order to filter out only the most accurate ratings. Using this two step method we can make a validation system that is dynamic and one that becomes more accurate with time.