ClaimViz: Visual Analytics for Identifying and Verifying Factual Claims

2020 IEEE Visualization Conference (VIS)(2020)

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摘要
Verifying a factual claim made by public figures, aka fact-checking, is a common task of the journalists in the newsrooms. One critical challenge that fact-checkers face is-they have to swift through a large amount of text to find claims that are check-worthy. While there exist some computational methods for automating the fact-checking process, little research has been done on how a system should combine such techniques with visualizations to assist fact-checkers. ClaimViz is a visual analytic system that integrates natural language processing and machine learning methods with interactive visualizations to facilitate the fact-checking process. The design of ClaimViz is based on analyzing the requirements of real fact-checkers and our case studies demonstrate how the system can help users to effectively spot and verify claims.
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Human-centered computing,Visualization,Visualization design and evaluation methods
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