Our project is a fake news detection system that uses Natural Language Processing (NLP) techniques to analyze news articles and determine their level of authenticity. We have developed a machine learning model that is trained on a large dataset of news articles, and uses features such as word frequency and topic modeling to identify patterns that are indicative of fake news.
To make our system accessible to users, we have built a web application using Flask, a popular Python web framework. The application allows users to submit news articles for analysis and receive a prediction on whether the article is likely to be fake or not. The application also provides visualizations of the data used in the analysis, such as word clouds and topic modeling graphs, to help users understand how the system arrived at its prediction.
Our goal with this project is to provide a tool that can help combat the spread of misinformation and fake news, and to promote greater awareness and critical thinking among news consumers.