Deep learning modeling of public’s sentiments towards temporal evolution of COVID-19 transmission

Public sentiments towards global pandemics are important for public health assessment and disease control. This study develops a modularized deep learning framework to quantify public sentiments towards COVID-19, followed by leveraging the predicted sentiments to model and forecast the daily growth...

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Detalles Bibliográficos
Autores principales: Wang, Ying, Chew, Alvin Wei Ze, Zhang, Limao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583649/
https://www.ncbi.nlm.nih.gov/pubmed/36281433
http://dx.doi.org/10.1016/j.asoc.2022.109728

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583649/
https://www.ncbi.nlm.nih.gov/pubmed/36281433
http://dx.doi.org/10.1016/j.asoc.2022.109728

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