{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:30:49Z","timestamp":1777455049830,"version":"3.51.4"},"reference-count":52,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Big Data &amp; Society"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>This study investigates the types of misinformation spread on Twitter that evokes scientific authority or evidence when making false claims about the antimalarial drug hydroxychloroquine as a treatment for COVID-19. Specifically, we examined tweets generated after former U.S. President Donald Trump retweeted misinformation about the drug using an unsupervised machine learning approach called the biterm topic model that is used to cluster tweets into misinformation topics based on textual similarity. The top 10 tweets from each topic cluster were content coded for three types of misinformation categories related to scientific authority: medical endorsements of hydroxychloroquine, scientific information used to support hydroxychloroquine\u2019s use, and a comparison group that included scientific evidence opposing hydroxychloroquine\u2019s use. Results show a much higher volume of tweets featuring medical endorsements and use of supportive scientific information compared to accurate and updated scientific evidence, that misinformation-related tweets propagated for a longer time frame, and the majority of hydroxychloroquine Twitter discourse expressed positive views about the drug. Metadata from Twitter accounts found that prominent users within misinformation discourse were more likely to have media or political affiliation and explicitly expressed support for President Trump. Conversely, prominent accounts within the scientific opposition discourse primarily consisted of medical doctors or scientists but had far less influence in the Twitter discourse. Implications of these findings and connections to related social media research are discussed, as well as cognitive mechanisms for understanding susceptibility to misinformation and strategies to combat misinformation spread via online platforms.<\/jats:p>","DOI":"10.1177\/20539517211013843","type":"journal-article","created":{"date-parts":[[2021,5,9]],"date-time":"2021-05-09T03:22:01Z","timestamp":1620530521000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":34,"title":["Identifying and characterizing scientific authority-related misinformation discourse about hydroxychloroquine on twitter using unsupervised machine learning"],"prefix":"10.1177","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4985-7796","authenticated-orcid":false,"given":"Michael Robert","family":"Haupt","sequence":"first","affiliation":[{"name":"Department of Cognitive Science, University of California San Diego, La Jolla, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9801-4715","authenticated-orcid":false,"given":"Jiawei","family":"Li","sequence":"additional","affiliation":[{"name":"Global Health Policy Institute, San Diego, USA"},{"name":"S-3 Research, San Diego, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2191-7833","authenticated-orcid":false,"given":"Tim K","family":"Mackey","sequence":"additional","affiliation":[{"name":"Global Health Policy Institute, San Diego, USA"},{"name":"S-3 Research, San Diego, USA"},{"name":"Department of Anesthesiology and Division of Infectious Diseases and Global Public Health, University of California, San Diego School of Medicine, San Diego, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2021,5,6]]},"reference":[{"key":"bibr1-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1804840115"},{"key":"bibr2-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1177\/0003122417733673"},{"key":"bibr3-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1177\/0956797615594620"},{"key":"bibr4-20539517211013843","unstructured":"Belluz J, Hoffman SJ (2013) Dr. Oz\u2019s Miraculous Medical Advice.\n                      Slate\n                      , 1 January. 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(2018) Twitter and the press: An ego-centred analysis. In: Companion proceedings of the web conference 2018, WWW\u201918, Republic and Canton of Geneva, CHE, 23 April 2018, pp.1471\u20131478. Geneva: International World Wide Web Conferences Steering Committee.","DOI":"10.1145\/3184558.3191596"},{"key":"bibr8-20539517211013843","unstructured":"Brenan M (2020) Americans\u2019 reported use of face masks surges in past week. Available at: https:\/\/news.gallup.com\/poll\/308678\/americans-reported-face-masks-surges-past-week.aspx (accessed 10 December 2020)."},{"key":"bibr9-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1093\/ijpor\/edl003"},{"key":"bibr10-20539517211013843","unstructured":"Cathey L (2020) Timeline: Tracking trump alongside scientific developments on hydroxychloroquine.\n                      ABC News\n                      . 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Available at: www.nytimes.com\/2020\/07\/28\/technology\/virus-video-trump.html (accessed 9 December 2020)."},{"key":"bibr16-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1002\/jcpy.1135"},{"key":"bibr17-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-5371(77)80012-1"},{"key":"bibr18-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1016\/j.osnem.2020.100114"},{"key":"bibr19-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1016\/j.concog.2011.08.018"},{"key":"bibr20-20539517211013843","doi-asserted-by":"publisher","DOI":"10.4269\/ajtmh.20-0812"},{"key":"bibr21-20539517211013843","doi-asserted-by":"publisher","DOI":"10.1037\/0278-7393.20.6.1420"},{"key":"bibr22-20539517211013843","doi-asserted-by":"crossref","unstructured":"Kahan DM (2017)\n                      Misconceptions, Misinformation, and the Logic of Identity-Protective Cognition\n                      . ID 2973067, SSRN Scholarly Paper, 24 May. 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New York: Association for Computing Machinery.","DOI":"10.1145\/2488388.2488514"}],"container-title":["Big Data &amp; Society"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/20539517211013843","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/20539517211013843","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/20539517211013843","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T12:58:11Z","timestamp":1777381091000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/20539517211013843"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1177\/20539517211013843"],"URL":"https:\/\/doi.org\/10.1177\/20539517211013843","relation":{},"ISSN":["2053-9517","2053-9517"],"issn-type":[{"value":"2053-9517","type":"print"},{"value":"2053-9517","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"article-number":"20539517211013843"}}