Track Mendacity Broadcast using Natural Language Processing

Abstract

Social media can be called as the powerhouse of news as it consists news from all the corners of the world and it’s a necessity for human life. Information sharing has become an easy task through social media and it has made our lives easier. But at the same time it unfocused on spreading of fake news in a faster rate. Fake broadcast is written purposefully to mislead readers to believe in false information. To decrease the misuse of news in the society an application is required which will help in identify and differentiate between fake and real news. Over the years numerous researcher has developed an application using different types of tools, techniques and algorithms to get best accuracy. Therefore, we are developing Track Mendacity Broadcast survey paper which is created in order to increase the accuracy of detecting mendacity broadcast more than the present solution available. This is a virtual application that works using Natural Language Processing and Machine Learning methods and algorithm. The Track Mendacity Broadcast paper work helps to identify the news and differentiate the news between false and true news by taking the input text from user and comparing it with already existing datasets which are available and also considers ratings and comments available for the given text news. This survey paper can be developed by using both unsupervised and supervised algorithms present in Natural Language Processing and accuracy of the news can be calculated with the help of the methods and equations available in Machine Learning. In addition, this paper considers different approaches available for this application.