Author: Swetland, Sarah B.; Rothrock, Ava N.; Andris, Halle; Davis, Bennett; Nguyen, Linh; Davis, Phil; Rothrock, Steven G.
Title: Accuracy of healthâ€related information regarding COVIDâ€19 on Twitter during a global pandemic Cord-id: cavymayk Document date: 2021_7_29
ID: cavymayk
Snippet: This study was performed to analyze the accuracy of healthâ€related information on Twitter during the coronavirus disease 2019 (COVIDâ€19) pandemic. Authors queried Twitter on three dates for information regarding COVIDâ€19 and five terms (cure, emergency or emergency room, prevent or prevention, treat or treatments, vitamins or supplements) assessing the first 25 results with healthâ€related information. Tweets were authoritative if written by governments, hospitals, or physicians. Two phys
Document: This study was performed to analyze the accuracy of healthâ€related information on Twitter during the coronavirus disease 2019 (COVIDâ€19) pandemic. Authors queried Twitter on three dates for information regarding COVIDâ€19 and five terms (cure, emergency or emergency room, prevent or prevention, treat or treatments, vitamins or supplements) assessing the first 25 results with healthâ€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 healthâ€related COVIDâ€19 tweets inaccurate indicating that the public should not rely on COVIDâ€19 health information written on Twitter. Ideally, improved government regulatory authority, public/private industry oversight, independent factâ€checking, and artificial intelligence algorithms are needed to ensure inaccurate information on Twitter is removed.
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