Published Paper Details:

As the world is growing towards Internet-based digitalization over the social media, millions of articles are uploaded every second, and the Internet users are more keep on social media applications such as WhatsApp, Meta, Instagram, Twitter and other online applications. The aim of the project is to detect the Fake or Real News in online available articles. There are many news channels online, who are publishing the daily news and more people read online media as it has many benefits such as paperless, fingertip availability of news, Attractive headlines and colorful titles. The recent advancement of the online social media platforms has impacted the daily life of civilization. The people who are using the above online news platform should not get the fake news regarding, we need to identify the challenging solution that can detect the fake news. The application of the Project is detecting the fake news using Machine Learning (ML) and Deep learning (DL). The project uses two major algorithms namely Passive Aggressive Classifier and Adaptive Boosting Classifier (ABC) and Long Short Term Memory (LSTM). We have made the strong analysis and visualization on the dataset supplied. Our models are providing 95% & above accuracy. Finally we have developed the Web Application for the prediction of Forged and Actual news.