ARCHIVES

This project develops a sentiment analysis system for election prediction by analyzing tweets about political leaders. The system uses machine learning, specifically a Passive Aggressive Classifier, along with text preprocessing techniques like TF-IDF vectorization to classify tweets as positive or negative. A Flask web application is built to allow users to upload a CSV file containing tweets, process the data, and visualize the sentiment distribution through a pie chart. The system provides insights into public sentiment, assisting in predicting election outcomes based on social media opinions.