Uncovering temporal differences in COVID-19 tweets.

Han Zheng, Dion H-L Goh, Chei S Lee, Edmund W J Lee, Yin L Theng
Author Information
  1. Han Zheng: Wee Kim Wee School of Communication and Information Nanyang Technological University Singapore.
  2. Dion H-L Goh: Wee Kim Wee School of Communication and Information Nanyang Technological University Singapore.
  3. Chei S Lee: Wee Kim Wee School of Communication and Information Nanyang Technological University Singapore.
  4. Edmund W J Lee: Wee Kim Wee School of Communication and Information Nanyang Technological University Singapore.
  5. Yin L Theng: Wee Kim Wee School of Communication and Information Nanyang Technological University Singapore.

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.

Keywords

References

  1. PLoS One. 2011 May 04;6(5):e19467 [PMID: 21573238]
  2. Ann Glob Health. 2017 May - Aug;83(3-4):682-690 [PMID: 29221545]
  3. PLoS One. 2010 Nov 29;5(11):e14118 [PMID: 21124761]
  4. PLoS One. 2013 Nov 27;8(11):e79449 [PMID: 24312181]
  5. Am J Public Health. 2017 Jan;107(1):e1-e8 [PMID: 27854532]
  6. IEEE Trans Pattern Anal Mach Intell. 1984 Jun;6(6):721-41 [PMID: 22499653]
  7. JMIR Public Health Surveill. 2020 May 29;6(2):e19273 [PMID: 32427106]
  8. Comput Human Behav. 2016 Jan 1;54:351-357 [PMID: 26392678]
  9. JAMA. 2015 Nov 17;314(19):2010-2 [PMID: 26575048]
  10. Proc Assoc Inf Sci Technol. 2020;57(1):e233 [PMID: 33173810]
  11. JMIR Public Health Surveill. 2017 Apr 20;3(2):e22 [PMID: 28428164]

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