Accuracy of health-related information regarding COVID-19 on Twitter during a global pandemic.

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH World Medical & Health Policy Pub Date : 2021-09-01 Epub Date: 2021-07-29 DOI:10.1002/wmh3.468
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 χ 2 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.

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在全球大流行期间,Twitter上与COVID-19相关的健康信息的准确性。
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
World Medical & Health Policy
World Medical & Health Policy PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
7.10
自引率
7.30%
发文量
65
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