{"id":25790727,"url":"https://github.com/royanikseresht/sentimentanalysis","last_synced_at":"2026-04-09T12:42:29.090Z","repository":{"id":278701551,"uuid":"936493497","full_name":"royanikseresht/SentimentAnalysis","owner":"royanikseresht","description":"A web application that analyzes the sentiment of user-provided text (positive, negative, or neutral) and displays the result with a confidence score. 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It also includes a **dark mode** toggle and an **About Me** section that can be accessed through a modal popup.\n\n## Features\n\n- **Sentiment Analysis**: The app analyzes the sentiment of the input text and displays the sentiment label (positive, negative, or neutral) along with a confidence score.\n- **Dark Mode**: The app provides a toggle button to switch between light and dark themes.\n- **About Me Modal**: An \"About Me\" section that opens in a modal, featuring a circular image and personal information. \n- **Prevent Right Click \u0026 Text Selection**: The app disables the ability to right-click and select text or images.\n\n## Screenshots\n\n![Screenshot 1](assets/app.png)\n\n\n## Technologies Used\n\n- **HTML**: Structure and content of the web page.\n- **CSS**: Styling, including responsive design and dark mode.\n- **JavaScript**: For interactivity, including the sentiment analysis request, dark mode toggle, and modal functionality.\n- **Python (Backend)**: A Flask server (or similar) that processes the sentiment analysis.\n\n## Installation\n\nTo run the project locally:\n\n1. Clone the repository to your local machine:\n   ```bash\n   git clone https://github.com/royanikseresht/sentimentanalysis.git\n   ```\n\n2. Navigate to the project folder:\n   ```bash\n   cd sentimentanalysis\n   ```\n\n3. Open the `index.html` file in your browser:\n   ```bash\n   open index.html  # MacOS\n   start index.html # Windows\n   xdg-open index.html  # Linux\n   ```\n\n4. Ensure the backend is running on `http://127.0.0.1:5000`. You may need to set up a simple backend server using Flask or similar for the sentiment analysis to work.\n\n   Example for Flask:\n   ```bash\n   pip install flask\n   ```\n\n   And create a `app.py`:\n   ```python\n   from flask import Flask, request, jsonify\n   from some_sentiment_analysis_module import analyze_sentiment\n\n   app = Flask(__name__)\n\n   @app.route('/analyze', methods=['POST'])\n   def analyze():\n       data = request.get_json()\n       text = data.get('text')\n       sentiment, score = analyze_sentiment(text)\n       return jsonify({'label': sentiment, 'score': score})\n\n   if __name__ == '__main__':\n       app.run(debug=True)\n   ```\n\n## How It Works\n\n### **1. Sentiment Analysis**\nThe app uses a backend API to perform sentiment analysis. Users input text, which is sent to the backend, and the sentiment label (positive, negative, neutral) along with a confidence score is returned and displayed on the web page.\n\n### **2. Dark Mode Toggle**\nThe app allows users to toggle between dark and light themes using a button at the top-right corner. This toggle is implemented with JavaScript, and the styles switch between a light mode and dark mode using a `.dark-mode` class.\n\n### **3. About Me Modal**\nThe \"About Me\" button opens a modal where users can learn more about the creator of the project. This modal is styled with rounded image and personal information.\n\n### **4. Prevent Right Click and Text Selection**\nThe app includes JavaScript to disable text selection and right-click functionality to prevent users from copying content.\n\n## Development\n\n### Frontend Development\n\nThe frontend is built using:\n- **HTML5** for the structure.\n- **CSS3** for responsive and theme-based styling.\n- **JavaScript** for user interactivity.\n\n### Backend Development\n\nThe backend (sentiment analysis) can be built using **Python** and **Flask** or any other backend technology that you prefer. The backend should expose an endpoint (`/analyze`) that accepts text and returns a sentiment label and score.\n\n## Contributing\n\nFeel free to fork this project and submit pull requests for any improvements or bug fixes.\n\n### Steps for contributing:\n1. Fork the repository\n2. Clone your fork locally\n3. Create a feature branch (`git checkout -b feature-branch`)\n4. Commit your changes (`git commit -m 'Add feature'`)\n5. Push to your branch (`git push origin feature-branch`)\n6. Create a pull request\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Froyanikseresht%2Fsentimentanalysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Froyanikseresht%2Fsentimentanalysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Froyanikseresht%2Fsentimentanalysis/lists"}