https://github.com/oussama-zbair/sentiment-analysis

Sentiment analysis tool scraping Arabic comments displaying results.
https://github.com/oussama-zbair/sentiment-analysis

beatifulsoup nltk-python python web-scraping

Last synced: 11 months ago
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Sentiment analysis tool scraping Arabic comments displaying results.

• Host: GitHub
• URL: https://github.com/oussama-zbair/sentiment-analysis
• Owner: oussama-zbair
• Created: 2024-05-07T08:34:45.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-05-21T07:45:10.000Z (about 2 years ago)
• Last Synced: 2025-06-25T05:03:23.503Z (11 months ago)
• Topics: beatifulsoup, nltk-python, python, web-scraping
• Language: Python
• Homepage:
• Size: 2.72 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Sentiment Analysis on Hespress Comments

![Python](https://img.shields.io/badge/python-%2314354C.svg?style=for-the-badge&logo=python&logoColor=white) ![Pandas](https://img.shields.io/badge/pandas-%23150458.svg?style=for-the-badge&logo=pandas&logoColor=white) ![Flask](https://img.shields.io/badge/flask-%23000.svg?style=for-the-badge&logo=flask&logoColor=white) ![NLTK](https://img.shields.io/badge/nltk-%230078d7.svg?style=for-the-badge&logo=nltk&logoColor=white) ![BeautifulSoup](https://img.shields.io/badge/beautifulsoup-%2314354C.svg?style=for-the-badge&logo=python&logoColor=white)

This web application allows users to analyze the sentiment of comments on Hespress articles. It fetches comments from a Hespress article and classifies them as positive, negative, or neutral based on their sentiment.

## Introduction

This tool allows you to analyze the sentiment of comments on Hespress articles. You can fetch comments from a Hespress article and analyze their sentiment to classify them as positive, negative, or neutral.

## Getting Started

To get started with the app, follow these steps:

1. Clone the repository to your local machine.

   **Clone the repository to your local machine:**

   ```bash

   git clone https://github.com/your-username/sentiment-analysis.git

   ```

2. Install the required dependencies by running

   ```bash

   pip install -r requirements.txt`

   ```

3. Run the Flask web server by executing `python app.py`.

4. Access the web app in your browser at `http://localhost:5000`.

5. Enter the URL of a Hespress article in the input field and click "Fetch and Analyze Comments".

## Usage

Once you've entered the URL of a Hespress article and clicked "Fetch and Analyze Comments", the app will display the sentiment analysis results, including the sentiment of each comment and a sentiment distribution chart.

## Contributing

Contributions are welcome! If you find any bugs or have suggestions for improvement, please open an issue or submit a pull request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.