Scraping Prepper-Ressources into AI-Text-Mining Pipeline

Project Overview

The PREP project is a sophisticated research platform that analyzes German-language crisis preparedness content at scale. I built a comprehensive system that scraped ~10,000 websites and applied advanced AI analysis to understand how communities prepare for emergencies.

Technical Architecture

Data Collection & Processing

• Automated web scraping pipeline with ethical compliance (robots.txt, rate limiting)
• AI-powered content analysis using GPT-4 for intelligent categorization
• Topic modeling with Python NLP libraries to discover emerging themes
• Structured data storage in MongoDB with advanced querying capabilities

Analysis & Visualization

• 13 primary content categories with 60+ detailed subcategories
• Interactive 3D network graphs showing content relationships (WebGL/D3.js)
• Real-time dashboard with statistics and filtering options
• Export functionality for academic research

Key Technologies

• Frontend: React, TypeScript, D3.js for 3D visualizations, Tailwind CSS
• Backend: Node.js, Express, MongoDB with optimized indexing
• AI Pipeline: Python, OpenAI GPT-4, spaCy, NLTK, Gensim for topic modeling
• Infrastructure: Docker containers, automated testing, comprehensive logging

Research Impact

This platform provides researchers with unprecedented insights into crisis communication patterns, information quality assessment, and regional differences in preparedness messaging across German-speaking communities. The tool has been instrumental in understanding how different groups approach emergency preparedness.