论文标题

他们真的发布了推文吗?查询事实检查网站和政治工作以确定推文错误

Did They Really Tweet That? Querying Fact-Checking Sites and Politwoops to Determine Tweet Misattribution

论文作者

Bradford, Caleb, Nelson, Michael L.

论文摘要

社交媒体帖子的屏幕截图已成为社交媒体网站上的普遍位置。虽然屏幕截图肯定有目的,但它们的无处不在,可以传播从未实际制作过的帖子的屏幕截图,从而扩大了错误贡献虚假信息。通过检测这种虚假信息的动机,我们研究了开发询问网络以获取推文存在的方法的方法。我们开发了使用所谓的推文到各种服务(Google,内置搜索和内置搜索的路透社)的搜索查询的软件,以查找事实检查文章和其他据称是推文的证据。我们还开发了工具,可以自动搜索网站PolitWoops,以获取可能由当选官员制作和删除的特定推文。 In addition, we developed software to scrape fact-check articles from the sites Reuters.com and Snopes.com in order to derive a ``truth rating" from any given article from these sites. For evaluation, we began the construction of a ground truth dataset of tweets with known evidence (currently only Snopes fact-check articles) on the live web, and we gathered MRR and P@1 values based on queries made using only the bodies of those推文。这些查询表明,内置的搜索有效地在MRR = 0.5500和P@1=0.5333的情况下找到适当的文章,而Google与网站一起使用:Snopes.com运营商通常在有问题的文章中有效,MRR = 0.8667和P@1=0.86667。

Screenshots of social media posts have become common place on social media sites. While screenshots definitely serve a purpose, their ubiquity enables the spread of fabricated screenshots of posts that were never actually made, thereby proliferating misattribution disinformation. With the motivation of detecting this type of disinformation, we researched developing methods of querying the Web for evidence of a tweet's existence. We developed software that automatically makes search queries utilizing the body of alleged tweets to a variety of services (Google, Snopes built-in search, and Reuters built-in search) in an effort to find fact-check articles and other evidence of supposedly made tweets. We also developed tools to automatically search the site Politwoops for a particular tweet that may have been made and deleted by an elected official. In addition, we developed software to scrape fact-check articles from the sites Reuters.com and Snopes.com in order to derive a ``truth rating" from any given article from these sites. For evaluation, we began the construction of a ground truth dataset of tweets with known evidence (currently only Snopes fact-check articles) on the live web, and we gathered MRR and P@1 values based on queries made using only the bodies of those tweets. These queries showed that the Snopes built-in search was effective at finding appropriate articles about half of the time with MRR=0.5500 and P@1=0.5333, while Google when used with the site:snopes.com operator was generally effective at finding the articles in question, with MRR=0.8667 and P@1=0.8667.

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