Uncovering temporal differences in COVID-19 tweets.
Proc Assoc Inf Sci Technol
; 57(1): e233, 2020.
Article
in English
| MEDLINE | ID: covidwho-919820
ABSTRACT
In the fight against the COVID-19 pandemic, understanding how the public responds to various initiatives is an important step in assessing current and future policy implementations. In this paper, we analyzed Twitter tweets using topic modeling to uncover the issues surrounding people's discussion of the disease. Our focus was on temporal differences in topics, prior and after the declaration of COVID-19 as a pandemic. Nine topics were identified in our analysis, each of which showed distinct levels of discussion over time. Our results suggest that as the pandemic progresses, the concerns of the public vary as new developments come to light.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Language:
English
Journal:
Proc Assoc Inf Sci Technol
Year:
2020
Document Type:
Article
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