Partisan Differences in Twitter Language Among US Legislators During the COVID-19 Pandemic: Cross-sectional Study.

Guntuku, Sharath Chandra; Purtle, Jonathan; Meisel, Zachary F; Merchant, Raina M; Agarwal, Anish

Guntuku, Sharath Chandra; Purtle, Jonathan; Meisel, Zachary F; Merchant, Raina M; Agarwal, Anish.

Afiliação

Guntuku SC; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.
Purtle J; Penn Medicine Center for Digital Health, University of Pennsylvania, Philadelphia, PA, United States.
Meisel ZF; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.
Merchant RM; Department of Health Management & Policy, Drexel University Dornsife School of Public Health, Philadelphia, PA, United States.
Agarwal A; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.

J Med Internet Res ; 23(6): e27300, 2021 06 03.

Article em En | MEDLINE | ID: mdl-33939620

Assuntos

COVID-19/epidemiologia; COVID-19/psicologia; Comunicação em Saúde; Mídias Sociais/estatística & dados numéricos; Estudos Transversais; Humanos; Idioma; Pandemias; SARS-CoV-2/isolamento & purificação; Estados Unidos/epidemiologia

Palavras-chave

COVID-19; Twitter; US legislators; content; cross-sectional; digital health; infodemiology; infoveillance; language; natural language processing; policy; policy makers; politics; sentiment; social media

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Comunicação em Saúde / Mídias Sociais / COVID-19 Tipo de estudo: Observational_studies / Prevalence_studies / Risk_factors_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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