Clickbait Detector is an innovative web application designed to help users identify and analyze potentially misleading news headlines. The frontend provides an intuitive interface for interacting with our machine learning-powered clickbait detection system.
- Framework: Next.js
- UI Components: Shadcn UI
- Animations: Framer Motion
- Language: TypeScript
- Styling: Tailwind CSS
- Real-time clickbait headline analysis
- Sleek and responsive user interface
- Smooth animations and interactions
- Detailed prediction results
- Modern, mobile-friendly design
Check out the backend application: Clickbait Detector Backend
https://living-madella-gedeapriana-2f6e9d4d.koyeb.app/
- Node.js 16+
- npm or yarn
- Clone the repository
git clone https://github.com/gdapriana/clickbait-detector-frontend.git
cd clickbait-detector-frontend
- Install dependencies
npm install
# or
yarn install
- Run the development server
npm run dev
# or
yarn dev
- Open http://localhost:3000 in your browser
npm run build
# or
yarn build
/src
├── app/ # Next.js routes
├── components/ # Reusable UI components
└── lib/ # Utility functions
Utilizes Shadcn UI for consistent and accessible design components:
- Responsive layouts
- Interactive form elements
- Modular and customizable UI kit
Powered by Framer Motion to create:
- Smooth page transitions
- Engaging interactive elements
- Subtle and meaningful animations
- User enters a news headline
- Frontend sends the headline to the backend API
- Machine learning model analyzes the text
- Results are displayed with prediction probability
Interested in contributing?
- Fork the repository
- Create a feature branch
git checkout -b feature/AmazingFeature
- Commit your changes
git commit -m 'Add some AmazingFeature'
- Push to the branch
git push origin feature/AmazingFeature
- Open a Pull Request
Distributed under the MIT License. See LICENSE
for more information.
For any questions or issues, please open an issue in the GitHub repository.
A passionate team of developers dedicated to creating intelligent web solutions.