Tweet-Sentiment-Extraction

A powerful Flask-based web application for analyzing sentiment in text using machine learning, featuring interactive visualizations and emoji reactions.

github.com

GitHub - nour43210/Tweet-Sentiment-Extraction

Contribute to nour43210/Tweet-Sentiment-Extraction development by creating an account on GitHub.

🚀 Multiple ML Models: Choose between Logistic Regression, Naive Bayes, SVM, and Random Forest

📊 Interactive Visualizations: Plotly charts for sentiment polarity and subjectivity

😊 Emoji Reactions: Instant visual feedback with sentiment emojis

☁️ Word Clouds: Beautiful visual representations of key terms

📈 Training History: Track model performance over time

📁 Model Management: Save and load trained models

🎨 Modern UI: Clean, responsive interface with animations

Installation

Clone the repository:

git clone https://github.com/yourusername/sentiment-analysis-app.git

cd sentiment-analysis-app

sentiment-analysis-app/

├── app.py # Main Flask application ├── requirements.txt # Python dependencies ├── README.md # This file ├── uploads/ # Folder for uploaded datasets └── templates/ └── enhanced_index.html # Enhanced HTML template

Requirements :

Python 3.8+

Flask

scikit-learn

nltk

pandas

wordcloud

matplotlib

plotly

textblob

how to run : use ( python app.py ) in the terminal

click on the image to see the project details ⬆️