A Machine Learning-Based Approach for Fake News Detection Using NLP and Web Technologies

The rapid expansion of digital communication hasprovided immense opportunities for the spread of informationbut has also posed a significant threat in the form of fake news.Fake news refers to false or misleading information presented asnews, which can have serious implications on public opinion,political stability, and societal trust. This research addressesthis challenge by developing a Fake News Detection Systemthat uses Natural Language Processing (NLP) and machinelearning. The system is deployed through a web-based platform,combining a React.js frontend with a Flask backend, andutilizes Logistic Regression for classification. With TF-IDF asa feature extraction method, our model achieves an accuracyof 92.5