Sarah B Swetland, Ava N Rothrock, Halle Andris, Bennett Davis, Linh Nguyen, Phil Davis, Steven G Rothrock
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引用次数: 11
Abstract
This study was performed to analyze the accuracy of health-related information on Twitter during the coronavirus disease 2019 (COVID-19) pandemic. Authors queried Twitter on three dates for information regarding COVID-19 and five terms (cure, emergency or emergency room, prevent or prevention, treat or treatments, vitamins or supplements) assessing the first 25 results with health-related information. Tweets were authoritative if written by governments, hospitals, or physicians. Two physicians assessed each tweet for accuracy. Metrics were compared between accurate and inaccurate tweets using χ2 analysis and Mann-Whitney U. A total of 25.4% of tweets were inaccurate. Accurate tweets were more likely written by Twitter authenticated authors (49.8% vs. 20.9%, 28.9% difference, 95% confidence interval [CI]: 17.7-38.2) with accurate tweet authors having more followers (19,491 vs. 7346; 3446 difference, 95% CI: 234-14,054) versus inaccurate tweet authors. Likes, retweets, tweet length, botometer scores, writing grade level, and rank order did not differ between accurate and inaccurate tweets. We found 1/4 of health-related COVID-19 tweets inaccurate indicating that the public should not rely on COVID-19 health information written on Twitter. Ideally, improved government regulatory authority, public/private industry oversight, independent fact-checking, and artificial intelligence algorithms are needed to ensure inaccurate information on Twitter is removed.
本研究旨在分析2019年冠状病毒病(COVID-19)大流行期间Twitter上与健康相关信息的准确性。作者在推特上查询了三个日期有关COVID-19的信息和五个术语(治愈、急诊或急诊室、预防或预防、治疗或治疗、维生素或补充剂),用与健康相关的信息评估了前25个结果。如果推特是由政府、医院或医生写的,那么它就是权威的。两名医生评估了每条推文的准确性。使用χ 2分析和Mann-Whitney u对准确和不准确推文的度量进行比较,共有25.4%的推文不准确。准确的推文更有可能由Twitter认证的作者撰写(49.8% vs. 20.9%,差异28.9%,95%置信区间[CI]: 17.7-38.2),准确的推文作者拥有更多的关注者(19,491 vs. 7346;3446差异,95% CI: 234-14,054)和不准确的推文作者。点赞数、转发数、推文长度、测底器得分、写作年级水平和排名顺序在准确和不准确的推文之间没有差异。我们发现1/4与COVID-19相关的推文是不准确的,这表明公众不应该依赖推特上写的COVID-19健康信息。理想情况下,需要改进政府监管机构、公共/私营行业监督、独立的事实核查和人工智能算法,以确保删除Twitter上的不准确信息。