🌍 Multilingual Sentiment Analysis Web App

Welcome to the Sentiment Analysis Web App! This application allows you to analyze sentiments in over 20 languages using advanced AI models from Hugging Face. It is built with Flask and provides a user-friendly interface for real-time sentiment analysis. Whether you are a developer, researcher, or just curious about sentiment trends, this app has something for you.

Table of Contents

• Features
• Technologies Used
• Installation
• Usage
• Contributing
• License
• Contact
• Releases

Features

• Multilingual Support: Analyze sentiments in over 20 languages.
• Real-Time Analysis: Get instant feedback on sentiment.
• Automatic Language Detection: The app detects the language of the input text automatically.
• Responsive UI: The user interface adjusts to different screen sizes, making it accessible on both desktop and mobile devices.
• Easy to Use: Simple input field for text and clear output display.

Technologies Used

• Flask: A lightweight WSGI web application framework for Python.
• Hugging Face: A platform for Natural Language Processing (NLP) models.
• Python: The primary programming language used for backend development.
• HTML/CSS: For front-end design and layout.
• JavaScript: For interactive elements and real-time updates.

Installation

To get started with the Sentiment Analysis Web App, follow these steps:

1. Clone the repository:

   git clone https://github.com/moonkl/Sentiment-Analysis-web-app.git
   cd Sentiment-Analysis-web-app

2. Install dependencies:

   Make sure you have Python and pip installed. Then run:

   pip install -r requirements.txt

3. Run the application:

   Start the Flask server with:

   python app.py

   The app will run on http://127.0.0.1:5000/.

Usage

1. Open your web browser and navigate to http://127.0.0.1:5000/.
2. Enter the text you want to analyze in the input field.
3. Click the "Analyze" button.
4. View the sentiment results displayed on the screen.

Contributing

We welcome contributions! If you want to help improve the app, please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add new feature').
5. Push to the branch (git push origin feature-branch).
6. Open a pull request.

License

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

Contact

For any inquiries, please reach out to the project maintainer:

• Name: Your Name
• Email: your.email@example.com
• GitHub: moonkl

Releases

For the latest updates and releases, please visit the Releases section. You can download the latest version of the app from there and execute it locally.

Screenshots

Home Page of the Sentiment Analysis Web App

Results Page showing sentiment analysis output

FAQs

What is Sentiment Analysis?

Sentiment analysis is a technique used to determine the emotional tone behind a series of words. It is commonly used to understand customer opinions, feedback, and trends in social media.

How does the app detect language?

The app uses advanced NLP models from Hugging Face to automatically identify the language of the input text. This feature allows users to input text without specifying the language.

Can I contribute to the project?

Yes, contributions are welcome! Please refer to the Contributing section for guidelines.

Is the app free to use?

Yes, the app is open-source and free to use. You can download it and run it on your local machine.

What if I encounter issues?

If you face any problems, please check the Issues section for existing reports or create a new issue.

Future Enhancements

We plan to add more features in the future, including:

• Support for more languages.
• Enhanced user interface with more interactive elements.
• Integration with social media platforms for real-time sentiment tracking.

Thank you for checking out the Sentiment Analysis Web App! We hope you find it useful for your sentiment analysis needs.