QuranicSentiment 🕌 ✨

An intelligent web application that provides relevant Quranic verses based on emotional states, combining sentiment analysis with spiritual guidance.

🌐 Live Site: https://ymorsi7.github.io/QuranicSentiment/

NOTE: This is NOT a ChatGPT wrapper 😂

Features 🌟

• Emotion Detection 🎭

  • Real-time analysis of user-inputted emotions
  • Support for both direct emotion selection and free-text input
  • Advanced sentiment analysis using VADER and TextBlob
  • Six primary emotional categories: Joyful, Peaceful, Fearful, Angry, Remorseful, and Reflective

• Verse Matching 📖

  • Intelligent matching of emotional states to relevant Quranic verses
  • Context-aware verse selection using both sentiment and linguistic analysis
  • Support for both exact and thematic emotional matches
  • Related verses suggestions based on content similarity

• User Interface 💫

  • Clean, modern, and responsive design
  • Intuitive emotion selection buttons
  • Smooth animations and transitions
  • Beautiful neumorphic styling

Technical Stack 🛠️

• Frontend:

  • HTML5, CSS3, JavaScript
  • Custom CSS animations and transitions
  • Responsive design with CSS Grid and Flexbox
  • Neumorphic UI components

• Backend:

  • Python 3.x
  • Flask web framework
  • Natural Language Processing:
    • VADER Sentiment Analysis
    • TextBlob
    • NLTK
  • Pandas for data processing

• Data:

  • JSON-based Quran database
  • Structured emotional word dictionaries
  • Sentiment mapping system

Machine Learning Pipeline 🧠

• Sentiment Analysis:

  • VADER scoring (neg, neu, pos, compound)

  • Custom linguistic feature extraction

  • Emotion-word dictionary mapping

• Model Performance:

  • 89% accuracy on verse classification

  • 0.87 F1 Score

  • 0.14 Balanced Error Rate

• Verse Classification:

  • Two-stage classification process

  • Multi-label emotion mapping

  • Confidence scoring system

Data Processing 📊

• Preprocessing:

  • Tokenization and lemmatization

  • Stopword removal

  • Feature extraction including sentiment polarity

• Dataset Statistics:

  • 6,236 total verses

  • 6 emotional categories

  • Distribution: 15% Joyful, 25% Peaceful, 10% Angry, 20% Fearful, 20% Remorseful, 10% Reflective

Installation 🚀

1. Clone the repository:

git clone https://github.com/ymorsi7/QuranicSentiment.git
cd QuranicSentiment

2. Install required Python packages:

pip install -r requirements.txt

3. Run the application:

python app.py

4. Open your browser and navigate to:

http://localhost:5000

Usage 📱

1. Direct Emotion Selection:

   • Click on any emotion button that matches your current feeling
   • Receive a relevant Quranic verse instantly

2. Text Input:

   • Type how you're feeling in the input box
   • Click "Analyze" or press Enter
   • The system will detect your emotion and provide a matching verse

3. Related Verses:

   • Explore similar verses shown below the main verse
   • Click on any related verse to view it

Emotional Categories 🎭

• Joyful 😊: Verses about happiness, gratitude, and divine blessings
• Peaceful 😌: Content focusing on tranquility, security, and inner peace
• Fearful 😨: Verses addressing anxiety, worry, and divine protection
• Angry 😠: Content about patience, self-control, and forgiveness
• Remorseful 😔: Verses about seeking forgiveness and divine mercy
• Reflective 🤔: Content encouraging contemplation and understanding

Project Structure 📁

QuranicSentiment/
├── docs/
│   ├── icon.png
│   ├── page.png
│   └── index.html
├── app.py
├── main.py
├── quran.json
└── README.md

Contributing 🤝

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License 📄

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments 🙏

• Quran data source
• VADER Sentiment Analysis
• TextBlob and NLTK communities
• All contributors and supporters

Contact 📬

Contributors:

• Yusuf Morsi
• Younus Ahmad
• Ali Alani

Project Links:

• Repository: https://github.com/ymorsi7/QuranicSentiment
• Live Site: https://ymorsi7.github.io/QuranicSentiment/