The Misinformation Early Warning Dashboard is designed to detect and classify fake news using machine
learning and natural language processing techniques. With the rapid growth of digital media, the spread
of misinformation has become a major challenge, affecting public awareness and decision-making. This
system allows users to input news content, which is then processed through text preprocessing and
feature extraction techniques such as CountVectorizer. A Naive Bayes algorithm is applied to classify the
news as real or fake based on learned patterns.
The results are displayed through an interactive dashboard, providing clear and immediate insights to
users. The system also maintains a history of analyzed news for tracking and future reference. It ensures
secure access through user authentication and provides a user-friendly interface. The proposed system
improves the speed and accuracy of misinformation detection compared to traditional methods. Overall,
it serves as an effective tool for early identification of fake news and supports users in making informed
decisions.
