Snopes Fact-Check Scraper

Scrape fact-check articles from Snopes.com with structured claim data, ratings, and full article text.

What it does

This scraper extracts Snopes fact-check articles using their RSS feed and listing pages for discovery, then scrapes individual articles to extract structured data from ClaimReview JSON-LD schema markup.

Output fields

Field	Description
title	Article headline
url	Full article URL
claim	The claim being fact-checked (from ClaimReview schema)
rating	Fact-check verdict: True, False, Mixture, Mostly True, Mostly False, Originated as Satire, etc.
ratingValue	Numeric rating value (when available)
author	Article author name
publishedAt	ISO 8601 publication date
modifiedAt	ISO 8601 last modified date
category	Article section (Politics, Science, News, etc.)
description	Brief article summary
imageUrl	Featured image URL
bodyText	Full article body text
tags	Array of tags and breadcrumb categories
scrapedAt	ISO 8601 scrape timestamp

Input options

• Category: Filter by category (All, Fact Checks, News, Science, Politics)
• Max Results: Maximum number of articles to scrape (1-1000, default 100)
• Proxy: Optional proxy configuration

Example output

{
  "title": "Did Trump promote new rules that would limit privileges for Congress members?",
  "url": "https://www.snopes.com/fact-check/trump-rules-congress/",
  "claim": "In 2026, U.S. President Donald Trump promoted a proposal called 'The TRUMP Rules' that would restrict legislative lawmakers' privileges and actions.",
  "rating": "False",
  "ratingValue": null,
  "author": "Rae Deng",
  "publishedAt": "2026-04-25T19:00:05Z",
  "modifiedAt": "2026-04-25T19:00:05Z",
  "category": "Politics",
  "description": "...",
  "imageUrl": "https://mediaproxy.snopes.com/width/1200/...",
  "bodyText": "...",
  "tags": ["Fact Checks", "Politics"],
  "scrapedAt": "2026-04-25T22:00:00.000Z"
}

Use cases

• Media monitoring: Track fact-check verdicts on trending claims
• Research datasets: Build corpora of verified/debunked claims for NLP research
• Misinformation tracking: Monitor the spread and debunking of false claims
• Content verification: Cross-reference claims against Snopes verdicts
• Trend analysis: Track what types of claims are being fact-checked over time

How it works

1. Discovery: Fetches the Snopes RSS feed and paginated listing pages to collect article URLs
2. Extraction: Scrapes each article page and parses ClaimReview + Article JSON-LD structured data
3. Fallbacks: Uses HTML selectors as backup when JSON-LD data is incomplete
4. Output: Pushes structured results to the Apify dataset

Cost

This actor uses pay-per-event pricing. You are charged $0.005 per result returned.