Improving Public Health Policy by Comparing the Public Response during the Start of COVID-19 and Monkeypox on Twitter in Germany: A Mixed Methods Study.

Al-Ahdal, Tareq; Coker, David; Awad, Hamzeh; Reda, Abdullah; Zuratynski, Przemyslaw; Khailaie, Sahamoddin

Al-Ahdal, Tareq; Coker, David; Awad, Hamzeh; Reda, Abdullah; Zuratynski, Przemyslaw; Khailaie, Sahamoddin.

Afiliação

Al-Ahdal T; Research Associate, Institute of Global Health (HIGH), Heidelberg University, 69117 Heidelberg, Germany.
Coker D; Advanced Education Programs, Adjunct Faculty, Fort Hays State University, Hays, KS 67601, USA.
Awad H; A/Professor Health Information Management and Health Informatics Research Chair, Higher College of Technology, Abu Dhabi 25026, United Arab Emirates.
Reda A; Faculty of Medicine, Al-Azhar University, Cairo 11651, Egypt.
Zuratynski P; Division of Medical Rescue, Faculty of Health Sciences with the Institute of Maritime and Tropical Medicine, Medical University of Gdansk, 80-210 Gdansk, Poland.
Khailaie S; Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, 38124 Braunschweig, Germany.

Vaccines (Basel) ; 10(12)2022 Nov 22.

Article em En | MEDLINE | ID: mdl-36560395

Palavras-chave

COVID-19; Natural Language Processing; monkeypox; public health policy; thematic analysis; unsupervised machine learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Qualitative_research Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Qualitative_research Idioma: En Ano de publicação: 2022 Tipo de documento: Article