Published Paper Details:

The rapid growth of social media platforms and digital communication channels has increased the spread of fake news across the world. False information shared through websites, blogs, and social media applications creates confusion among users and negatively affects society, politics, education, and public health. Manual verification of news articles is time-consuming and difficult due to the large amount of online content generated every day. This research paper presents a Fake News Detection Web Platform that uses Machine Learning and Natural Language Processing (NLP) techniques to identify whether a news article is real or fake. The proposed system allows users to enter news content through a web interface, after which the system analyzes the text using trained machine learning models. The platform provides accurate and fast predictions with a user-friendly interface. The research also discusses system architecture, methodology, dataset processing, algorithms used, advantages, limitations, and future improvements. The developed platform can help users verify online information and reduce the spread of misinformation.