{"id":22381035,"url":"https://github.com/gdapriana/clickbait-detector-backend","last_synced_at":"2026-04-11T19:35:52.545Z","repository":{"id":264347052,"uuid":"893108097","full_name":"gdapriana/clickbait-detector-backend","owner":"gdapriana","description":"This repository contains the backend logic for the “Clickbait Detector” app. Built using Python, it employs an Artificial Neural Network (ANN) to predict the likelihood of a news headline being clickbait. 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This project aims to help users distinguish between genuine and sensationalist news headlines.\n\n## 🚀 Technologies Used\n\n- **Programming Language**: Python\n- **Machine Learning Frameworks**:\n    - TensorFlow\n    - Scikit-learn\n- **Data Processing**:\n    - NLTK\n    - Pandas\n    - NumPy\n- **Web Framework**: Flask\n\n## 🔗 API Endpoints\n\n| Endpoint | Method | Description |\n|----------|--------|-------------|\n| `/dataset` | GET | Retrieve information about the dataset |\n| `/model` | GET | Get details about the machine learning model |\n| `/member` | GET | View information about the team |\n| `/tech` | GET | Learn about technologies used |\n| `/predict` | POST | Predict clickbait probability |\n\n### Prediction Endpoint Example\n```json\nPOST /predict\nRequest Body:\n{\n  \"text\": \"Your headline text to be analyzed\"\n}\n```\n\n## 🌐 Base URL\n```\nhttps://living-madella-gedeapriana-2f6e9d4d.koyeb.app/\n```\n\n## 🤝 Frontend Repository\nCheck out the frontend application:\n[Clickbait Detector Frontend](https://github.com/gdapriana/clickbait-detector-frontend)\n\n## 📦 Installation\n\n### Prerequisites\n- Python 3.10+\n- pip\n\n### Steps\n1. Clone the repository\n```bash\ngit clone \u003crepository-url\u003e\ncd clickbait-detector-backend\n```\n\n2. Create virtual environment\n```bash\npython -m venv venv\nsource venv/bin/activate  # On Windows use `venv\\Scripts\\activate`\n```\n\n3. Install dependencies\n```bash\npip install -r requirements.txt\n```\n\n4. Run the application\n```bash\npython app.py\n```\n\n## 🤖 How It Works\nThe Clickbait Detector uses machine learning models trained on a comprehensive dataset to analyze news headlines. It applies natural language processing techniques to determine the likelihood of a headline being clickbait.\n\n## 🛡️ Contributing\nInterested in contributing? Great!\n1. Fork the repository\n2. Create your feature branch (`git checkout -b feature/AmazingFeature`)\n3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)\n4. Push to the branch (`git push origin feature/AmazingFeature`)\n5. Open a Pull Request\n\n## 📄 License\nDistributed under the MIT License. See `LICENSE` for more information.\n\n## 👥 Team\nFor more information about the team, visit the `/member` endpoint of the API.\n\n## 🔍 Support\nFor any questions or issues, please open an issue in the GitHub repository.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgdapriana%2Fclickbait-detector-backend","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgdapriana%2Fclickbait-detector-backend","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgdapriana%2Fclickbait-detector-backend/lists"}