Social Media Misinformation Dataset Management (SMDM) 🔍

Overview 📋

The Social Media Misinformation Dataset Management (SMDM) project provides a robust solution for tracking and analyzing misinformation across social media platforms. Our system offers sophisticated tools for researchers, policymakers, and analysts to understand misinformation dynamics and develop effective countermeasures.

Features ✨

• 📊 Advanced Data Management

  • Scalable database architecture
  • Real-time data updates
  • Robust security measures
  • Data integrity validation

• 🔍 Analysis Capabilities

  • Misinformation pattern detection
  • Source tracking
  • Spread analysis
  • Impact assessment

• 🛡️ Security & Compliance

  • Data encryption
  • Access control
  • Audit logging
  • Privacy protection

Project Structure 🏗️

smdm/
├── templates/           # HTML templates
├── Create.sql          # Database schema
├── app1.py             # Main application
├── image.jpg           # Project assets
└── misinformation_data.csv  # Sample dataset

Installation 🚀

Prerequisites

• Python 3.7+
• PostgreSQL
• Web browser

Setup Instructions

1. Clone the repository:

git clone https://github.com/Siddhant231xyz/-Social-Media-Misinformation-Dataset-Collection-and-Management-SMDM-.git
cd smdm

2. Create virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Set up the database:

psql -U postgres -f Create.sql

Usage Guide 📚

1. Start the application:

python app1.py

2. Access the web interface:
   • Open your browser
   • Navigate to http://localhost:5000
   • Log in with your credentials

Key Components 🔧

• Database Layer: PostgreSQL for robust data storage
• Application Layer: Python-based backend
• Web Interface: User-friendly frontend
• Analytics Engine: Real-time data processing

Contributing 🤝

We welcome contributions! To contribute:

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

Please review our Contributing Guidelines before submitting PRs.

Roadmap 🛣️

• Enhanced visualization tools
• API integration
• Machine learning implementation
• Advanced reporting features
• Mobile application development

Documentation 📖

For detailed documentation and API references, visit our Wiki.

License 📝

This project is licensed under the MIT License - see the LICENSE file for details.

Team 👥

Our dedicated team of developers, researchers, and analysts work together to maintain and improve SMDM.

Acknowledgments 🙏

• Research partners
• Contributing organizations
• Open-source community

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Developed with dedication by the SMDM Team