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Exploring Coronavirus Disease 2019 Vaccine Hesitancy on Twitter Using Sentiment Analysis and Natural Language Processing Algorithms.
Bari, Anasse; Heymann, Matthias; Cohen, Ryan J; Zhao, Robin; Szabo, Levente; Apas Vasandani, Shailesh; Khubchandani, Aashish; DiLorenzo, Madeline; Coffee, Megan.
Afiliação
  • Bari A; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, New York, USA.
  • Heymann M; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, New York, USA.
  • Cohen RJ; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, New York, USA.
  • Zhao R; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, New York, USA.
  • Szabo L; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, New York, USA.
  • Apas Vasandani S; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, New York, USA.
  • Khubchandani A; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, New York, USA.
  • DiLorenzo M; Grossman School of Medicine, Department of Medicine, Division of Infectious Diseases and Immunology, New York University, New York, New York, USA.
  • Coffee M; Grossman School of Medicine, Department of Medicine, Division of Infectious Diseases and Immunology, New York University, New York, New York, USA.
Clin Infect Dis ; 74(Suppl_3): e4-e9, 2022 05 15.
Article em En | MEDLINE | ID: mdl-35568473
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article