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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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| Foilsithe in: | PLoS One |
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| Main Authors: | , , , , , |
| Formáid: | Artigo |
| Teanga: | Inglês |
| Foilsithe: |
Public Library of Science
2020
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| Ábhair: | |
| Rochtain Ar Líne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7518625/ https://ncbi.nlm.nih.gov/pubmed/32976519 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0239441 |
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