Computational Fact-checking
Datasets, models and visual analytics that help fact-checkers find check-worthy claims and verify them.
Project and papers →Research
Projects
Our work groups into 7 lines of research. Each project page lists its papers, which update automatically from Google Scholar.
Misleading Information and Clickbait
Detecting misleading headlines and clickbait in text and video, and testing corrections that stay honest without losing readers.
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Computational Framing Analysis
Unsupervised methods that find how news and social media frame an issue, at a scale manual coding cannot reach.
Project and papers →NewsBot: AI for News Audiences
What journalists and readers want from AI tools for news, starting with chatbots that answer readers' questions.
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Health Misinformation
How reliable and unreliable outlets report health news, automatic quality assessment, and health misinformation on social platforms.
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The #MeToo Project
Large-scale analysis of #MeToo and #WhyIDidntReport posts to understand survivors' experiences and why many never report.
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Sustainable Fact-checking
Fact-checking models that combine crowds, professionals and automated tools, and the challenges fact-checkers face in the Global South.
Project and papers →