An interactive web application utilizing machine learning techniques to identify and flag fabricated news articles.

In today's technological era, humans who use mobile phones, laptops and other electronic devices prefer reading news online. News organizations play a crucial role in delivering news and providing reliable sources. However, the main concern lies in the authentication of stories, articles shared online like whatsapp, Instagram handles, twitter, medium, Snapchat & various other social media. The acceptance of rumors disguised as news poses a significant risk to society, particularly in developing nations such as India, where countering rumors and focusing on truthful and verified information is essential. Distinguishing misleading or deceptive written articles is a complex task that cannot be easily automated. It is essential for professionals in particular domains to evaluate various aspects before forming opinions on the reliability of information. This endeavor suggests the implementation of a machine learning technique for the automatic categorization of news articles. The goal is to investigate different textual features that can be employed to distinguish between fake news and authentic news. [ABSTRACT FROM AUTHOR]