Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak

This study aims to conduct text mining of affective valence of the sentiments generated on social media during the COVID-19 and measure their association with different outcomes of the disease. 50,000 tweets per day over 23 days during the pandemic were extracted using the VADER sentiment analysis t...

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Detalles Bibliográficos
Autores principales: Mittal, Ruchi, Mittal, Amit, Aggarwal, Ishan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548272/
https://www.ncbi.nlm.nih.gov/pubmed/34721721
http://dx.doi.org/10.1007/s13278-021-00828-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548272/
https://www.ncbi.nlm.nih.gov/pubmed/34721721
http://dx.doi.org/10.1007/s13278-021-00828-x

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