Tweet Emotion Analyzer

Project Overview

Practical NLP application for social media sentiment analysis with multiple ML model options and visual feedback.

Key Features

• Streamlit interface for live sentiment classification
• Model switching: Naive Bayes, Logistic Regression, SVM
• TF-IDF and bi-gram modeling for enhanced accuracy
• Visual feedback and confidence scoring

Impact & Results

Practical application of NLP for social media sentiment analysis.