Interactive Web App for Fake News Detection

Abstract

In the contemporary era of technology, individuals who utilize mobile phones and laptops have developed a preference for accessing news through online media. News organizations disseminate news and offer confirmation sources. However, the issue at hand is how to authenticate stories and articles shared on social networks such as WhatsApp groups, Facebook pages, Twitter, and other smaller blogs and social networking sites. It is hazardous for society to accept rumours disguised as news, especially in developing nations like India, where it is crucial to prevent rumours and specialize in honest and verified information. Classifying written articles as misleading or deceptive is not easy to automate, and even experts in a specific field must evaluate several factors before rendering a judgment regarding the validity of a message. This project proposes the use of a machine learning approach to automatically classify news articles. This endeavour explores numerous text characteristics that can be employed to differentiate fabricated news content from actual news.