CovidChloroV1, Main, Corpus, bibRecord, 000428

Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter.

Identifieur interne : 000428 ( Main/Corpus ); précédent : 000427; suivant : 000429

Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter.

Auteurs : Tim K. Mackey ; Vidya Purushothaman ; Michael Haupt ; Matthew C. Nali ; Jiawei Li

Source :

The Lancet. Digital health [ 2589-7500 ] ; 2021.

RBID : pubmed:33509386

English descriptors

KwdEn :
- COVID-19 (drug therapy), Communication (MeSH), Humans (MeSH), Hydroxychloroquine (MeSH), Internet Use (MeSH), Machine Learning (MeSH), Quackery (MeSH), Social Media (MeSH), Unsupervised Machine Learning (MeSH).
MESH :
- chemical : Hydroxychloroquine.
- drug therapy : COVID-19.
- Communication, Humans, Internet Use, Machine Learning, Quackery, Social Media, Unsupervised Machine Learning.

DOI: 10.1016/S2589-7500(20)30318-6
PubMed: 33509386

Links to Exploration step

pubmed:33509386

Le document en format XML

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<author><name sortKey="Mackey, Tim K" sort="Mackey, Tim K" uniqKey="Mackey T" first="Tim K" last="Mackey">Tim K. Mackey</name>
<affiliation><nlm:affiliation>Department of Anesthesiology and Division of Infectious Disease and Global Public Health, University of California, San Diego, San Diego, CA 92037, USA; Department of Healthcare Research and Policy, University of California, San Diego, San Diego, CA 92037, USA; Global Health Policy Institute, San Diego, CA, USA; S-3 Research, San Diego, CA, USA. Electronic address: tmackey@ucsd.edu.</nlm:affiliation>
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<author><name sortKey="Purushothaman, Vidya" sort="Purushothaman, Vidya" uniqKey="Purushothaman V" first="Vidya" last="Purushothaman">Vidya Purushothaman</name>
<affiliation><nlm:affiliation>Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA 92037, USA; Global Health Policy Institute, San Diego, CA, USA.</nlm:affiliation>
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<author><name sortKey="Haupt, Michael" sort="Haupt, Michael" uniqKey="Haupt M" first="Michael" last="Haupt">Michael Haupt</name>
<affiliation><nlm:affiliation>Department of Cognitive Science, University of California, San Diego, San Diego, CA 92037, USA.</nlm:affiliation>
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<author><name sortKey="Nali, Matthew C" sort="Nali, Matthew C" uniqKey="Nali M" first="Matthew C" last="Nali">Matthew C. Nali</name>
<affiliation><nlm:affiliation>Department of Anesthesiology and Division of Infectious Disease and Global Public Health, University of California, San Diego, San Diego, CA 92037, USA; Global Health Policy Institute, San Diego, CA, USA; S-3 Research, San Diego, CA, USA.</nlm:affiliation>
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<author><name sortKey="Li, Jiawei" sort="Li, Jiawei" uniqKey="Li J" first="Jiawei" last="Li">Jiawei Li</name>
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<author><name sortKey="Haupt, Michael" sort="Haupt, Michael" uniqKey="Haupt M" first="Michael" last="Haupt">Michael Haupt</name>
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<author><name sortKey="Li, Jiawei" sort="Li, Jiawei" uniqKey="Li J" first="Jiawei" last="Li">Jiawei Li</name>
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<series><title level="j">The Lancet. Digital health</title>
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<term>Communication (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Hydroxychloroquine (MeSH)</term>
<term>Internet Use (MeSH)</term>
<term>Machine Learning (MeSH)</term>
<term>Quackery (MeSH)</term>
<term>Social Media (MeSH)</term>
<term>Unsupervised Machine Learning (MeSH)</term>
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<keywords scheme="MESH" type="chemical" xml:lang="en"><term>Hydroxychloroquine</term>
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</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Communication</term>
<term>Humans</term>
<term>Internet Use</term>
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<Month>03</Month>
<Day>18</Day>
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<DateRevised><Year>2021</Year>
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<JournalIssue CitedMedium="Internet"><Volume>3</Volume>
<Issue>2</Issue>
<PubDate><Year>2021</Year>
<Month>02</Month>
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<Title>The Lancet. Digital health</Title>
<ISOAbbreviation>Lancet Digit Health</ISOAbbreviation>
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<ArticleTitle>Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter.</ArticleTitle>
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	Serveur d'exploration COVID et hydrochloroquine
	Attention, ce site est en cours de développement ! Attention, site généré par des moyens informatiques à partir de corpus bruts. Les informations ne sont donc pas validées.

Serveur d'exploration COVID et hydrochloroquine

Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter.

Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter.

Source :

English descriptors

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki