Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter

The study aims to understand Twitter users’ discourse and psychological reactions to COVID-19. We use machine learning techniques to analyze about 1.9 million Tweets (written in English) related to coronavirus collected from January 23 to March 7, 2020. A total of salient 11 topics are identified an...

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Detalles Bibliográficos
Autores principales: Xue, Jia, Chen, Junxiang, Chen, Chen, Zheng, Chengda, Li, Sijia, Zhu, Tingshao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518625/
https://www.ncbi.nlm.nih.gov/pubmed/32976519
http://dx.doi.org/10.1371/journal.pone.0239441

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518625/
https://www.ncbi.nlm.nih.gov/pubmed/32976519
http://dx.doi.org/10.1371/journal.pone.0239441

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