Estimating time-series changes in social sentiment @Twitter in U.S. metropolises during the COVID-19 pandemic

Since early 2020, the global coronavirus pandemic has strained economic activities and traditional lifestyles. For such emergencies, our paper proposes a social sentiment estimation model that changes in response to infection conditions and state government orders. By designing mediation keywords th...

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Detalles Bibliográficos
Autores principales: Saito, Ryuichi, Haruyama, Shinichiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9660099/
https://www.ncbi.nlm.nih.gov/pubmed/36405087
http://dx.doi.org/10.1007/s42001-022-00186-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9660099/
https://www.ncbi.nlm.nih.gov/pubmed/36405087
http://dx.doi.org/10.1007/s42001-022-00186-4

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