How to Build a Disinformation Tracker with Web Scraping

How to Build a Disinformation Tracker with Web Scraping Disinformation spreads faster than fact-checks can keep up. Researchers, journalists, and analysts need automated tools to monitor narratives across the web. In this guide, we'll build a Python-based disinformation tracker that scrapes news sources, detects recurring false claims, and flags coordinated behavior patterns. Why Track Disinformation Programmatically? Manual monitoring doesn't scale. A single false claim can appear on hundreds of sites within hours. By scraping multiple sources simultaneously, you can detect patterns that human analysts would miss — like identical phrasing across unrelated domains or synchronized posting times. Architecture Overview Our tracker has three components: Multi-source scraper — collects articles from news sites and aggregators Similarity engine — detects duplicate/near-duplicate content across sources Timeline analyzer — identifies coordinated posting patterns Setting Up the Scraper First, i