A sophisticated AI-powered system for detecting fake news and misinformation using advanced natural language processing, fact verification, and source reliability analysis.
- Content Analysis Engine: Advanced NLP analysis detecting manipulative language patterns, emotional manipulation, and suspicious content structures
- Fact Verification System: Cross-references claims against trusted databases and knowledge sources
- Source Reliability Checker: Evaluates domain reputation, technical indicators, and bias detection
- Comprehensive Scoring Algorithm: Weighted credibility assessment combining all analysis components
- Professional Interface: Clean, trustworthy design with intuitive tabbed results layout
- Dark/Light Mode: Seamless theme switching with animated starfall background effects
- Real-time Analysis: Instant credibility assessment with detailed breakdowns
- Visual Indicators: Clear credibility scores, confidence intervals, and risk assessments
- RESTful API: Complete programmatic access to all detection capabilities
- Batch Processing: Analyze multiple texts simultaneously
- Individual Components: Access specific analysis modules independently
- Comprehensive Documentation: Built-in API documentation and health monitoring
- Node.js 18+
- npm or yarn package manager
-
Clone the repository ```bash git clone https://github.com/AyushSingh360/misinformation-detection.git cd misinformation-detection ```
-
Install dependencies ```bash npm install
yarn install ```
-
Run the development server ```bash npm run dev
yarn dev ```
-
Open your browser Navigate to http://localhost:3000
- Text Analysis: Paste or type content into the main input area
- URL Analysis: Enter a URL to analyze web content directly
- View Results: Explore detailed analysis across multiple tabs:
- Overview: Overall credibility score and classification
- Content Analysis: NLP insights and pattern detection
- Fact Check: Claim verification and evidence assessment
- Source Check: Domain reliability and technical analysis
```bash
curl -X POST http://localhost:3000/api/analyze
-H "Content-Type: application/json"
-d '{"text": "Your content to analyze", "url": "optional-source-url"}'
```
```bash
curl -X POST http://localhost:3000/api/content-analysis
-H "Content-Type: application/json"
-d '{"text": "Content to analyze"}'
curl -X POST http://localhost:3000/api/fact-check
-H "Content-Type: application/json"
-d '{"text": "Claims to verify"}'
curl -X POST http://localhost:3000/api/source-check
-H "Content-Type: application/json"
-d '{"url": "https://example.com"}'
```
```bash
curl -X POST http://localhost:3000/api/batch
-H "Content-Type: application/json"
-d '{"items": [{"text": "First text"}, {"text": "Second text"}]}'
```
- Next.js 14: React framework with App Router
- Tailwind CSS: Utility-first styling with custom design system
- Custom Theme System: Light/dark mode with animated backgrounds
- Responsive Design: Mobile-first approach with professional UI
- API Routes: RESTful endpoints for all detection services
- Analysis Engines: Modular NLP and verification systems
- Scoring Algorithm: Weighted credibility assessment
- Health Monitoring: System status and performance tracking
- Natural Language Processing: Advanced text analysis and pattern detection
- Fact Verification: Knowledge base integration and claim validation
- Source Analysis: Domain reputation and technical assessment
- Real-time Processing: Instant analysis with comprehensive results
- Primary: Professional blue (#2563eb)
- Success: Reliable green (#059669)
- Warning: Caution amber (#d97706)
- Danger: Alert red (#dc2626)
- Neutrals: Sophisticated grays with proper contrast ratios
- Headings: Inter font family with multiple weights
- Body: Optimized for readability with proper line heights
- Accessibility: WCAG AA compliant contrast ratios
```env
NEXT_PUBLIC_APP_URL=http://localhost:3000 ```
- Scoring Weights: Modify
components/credibility-scorer.tsx - Analysis Parameters: Update individual analysis components
- UI Themes: Customize
app/globals.csscolor variables - API Endpoints: Extend
app/api/directory
```bash
npm test
npm run test:coverage
npm run test:e2e ```
- Analysis Speed: < 2 seconds for typical content
- API Response: < 500ms average response time
- Accuracy: High precision with multi-layered verification
- Scalability: Designed for concurrent analysis requests
We welcome contributions! Please see our Contributing Guidelines for details.
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
This project is licensed under the MIT License - see the LICENSE file for details.
- Deployed on Vercel - The platform for frontend developers
- Inspired by the need for reliable information in the digital age
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Documentation: API Docs
- Live Demo: https://vercel.com/ash-a4f55268/v0-no-title
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