Fake News Detection Using Machine Learning

In today’s digital age, the rapid dissemination of information through online platforms has led to a significant rise in the spread of fake news. Misinformation can influence public opinion, disrupt societal harmony, and lead to real-world consequences. To combat this growing issue, this project presents a Fake News Detection System using Natural Language Processing (NLP) and Machine Learning techniques, deployed via a user-friendly Flask web application,The system allows users to input a news statement through a web interface. The input is preprocessed using tokenization, lemmatization, and removal of stop words. A pre-trained TF-IDF vectorizer converts the cleaned text into numerical format, which is then fed into a Passive Aggressive Classifier to determine the authenticity of the news. The model predicts whether the news is real or fake, and the result is instantly displayed on the webpage,This solution aims to empower users by providing a quick and reliable tool to validate news content, thereby promoting digital literacy and reducing the impact of misinformation in society.