The leading dataset for studying online misinformation and disinformation

NewsGuard data powers research studying misinformation, electoral integrity, media literacy, and other aspects of online news consumption habits. Our news source Reliability Ratings offer an independent, constantly-updated benchmark of news quality, and our Misinformation Fingerprints provide a curated catalog of the major misinformation narratives spreading online — and the sources that promote them.

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Current and past partners

“[NewsGuard] offers what appears to be the most comprehensive data on website credibility that has been assembled to date. We expect that it will prove essential in our research.”

Brendan Nyhan

James O. Freedman Presidential Professor, Department of Government, Dartmouth College

“We use NewsGuard because it provides more detailed information on the type of reporting each site carries out than other raters, while being widely used in academic work and very highly correlated with other rating agencies.”

Researchers at Microsoft's AI for Good Lab and Princeton University who used NewsGuard data to study how website referrals on unreliable websites create rabbit holes

White Paper

Research Backing NewsGuard's Reliability Ratings

This white paper summarizes research into misinformation's impact and potential solutions, illustrating how NewsGuard offers an effective approach backed by research. The paper also describes research projects that have been conducted using NewsGuard data.

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Case Study

Read about NewsGuard's data and the "Iffy" Quotient

The University of Michigan’s School of Information Center for Social Media Responsibility created a metric called the “Iffy Quotient,” which uses NewsGuard data and measures the percentage of the most popular news URLs on Facebook and Twitter that are from “iffy” sites that frequently publish unreliable information.

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Case Study

Analyzing Content Recommendation Algorithms

Researchers at Dartmouth, Indiana, and South Florida use NewsGuard’s Index to develop improved content recommendation algorithms. A project led by Brendan Nyhan from Dartmouth College, Giovanni Luca Ciampaglia from the University of South Florida, and Filippo Menczer and Alessandro Flammini from Indiana University used the Index to study how to improve the diversity of information circulating on social media.

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