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Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method

The COVID-19 pandemic has been sweeping across the United States of America since early 2020. The whole world was waiting for vaccination to end this pandemic. Since the approval of the first vaccine by the U.S. CDC on 9 November 2020, nearly 67.5% of the US population have been fully vaccinated by...

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Autores principales: Wang, Zifu, Chen, Yudi, Li, Yun, Kakkar, Devika, Guan, Wendy, Ji, Wenying, Cain, Jacob, Lan, Hai, Sha, Dexuan, Liu, Qian, Yang, Chaowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504395/
https://www.ncbi.nlm.nih.gov/pubmed/36146564
http://dx.doi.org/10.3390/vaccines10091486
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author Wang, Zifu
Chen, Yudi
Li, Yun
Kakkar, Devika
Guan, Wendy
Ji, Wenying
Cain, Jacob
Lan, Hai
Sha, Dexuan
Liu, Qian
Yang, Chaowei
author_facet Wang, Zifu
Chen, Yudi
Li, Yun
Kakkar, Devika
Guan, Wendy
Ji, Wenying
Cain, Jacob
Lan, Hai
Sha, Dexuan
Liu, Qian
Yang, Chaowei
author_sort Wang, Zifu
collection PubMed
description The COVID-19 pandemic has been sweeping across the United States of America since early 2020. The whole world was waiting for vaccination to end this pandemic. Since the approval of the first vaccine by the U.S. CDC on 9 November 2020, nearly 67.5% of the US population have been fully vaccinated by 10 July 2022. While quite successful in controlling the spreading of COVID-19, there were voices against vaccines. Therefore, this research utilizes geo-tweets and Bayesian-based method to investigate public opinions towards vaccines based on (1) the spatiotemporal changes in public engagement and public sentiment; (2) how the public engagement and sentiment react to different vaccine-related topics; (3) how various races behave differently. We connected the phenomenon observed to real-time and historical events. We found that in general the public is positive towards COVID-19 vaccines. Public sentiment positivity went up as more people were vaccinated. Public sentiment on specific topics varied in different periods. African Americans’ sentiment toward vaccines was relatively lower than other races.
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spelling pubmed-95043952022-09-24 Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method Wang, Zifu Chen, Yudi Li, Yun Kakkar, Devika Guan, Wendy Ji, Wenying Cain, Jacob Lan, Hai Sha, Dexuan Liu, Qian Yang, Chaowei Vaccines (Basel) Article The COVID-19 pandemic has been sweeping across the United States of America since early 2020. The whole world was waiting for vaccination to end this pandemic. Since the approval of the first vaccine by the U.S. CDC on 9 November 2020, nearly 67.5% of the US population have been fully vaccinated by 10 July 2022. While quite successful in controlling the spreading of COVID-19, there were voices against vaccines. Therefore, this research utilizes geo-tweets and Bayesian-based method to investigate public opinions towards vaccines based on (1) the spatiotemporal changes in public engagement and public sentiment; (2) how the public engagement and sentiment react to different vaccine-related topics; (3) how various races behave differently. We connected the phenomenon observed to real-time and historical events. We found that in general the public is positive towards COVID-19 vaccines. Public sentiment positivity went up as more people were vaccinated. Public sentiment on specific topics varied in different periods. African Americans’ sentiment toward vaccines was relatively lower than other races. MDPI 2022-09-07 /pmc/articles/PMC9504395/ /pubmed/36146564 http://dx.doi.org/10.3390/vaccines10091486 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Zifu
Chen, Yudi
Li, Yun
Kakkar, Devika
Guan, Wendy
Ji, Wenying
Cain, Jacob
Lan, Hai
Sha, Dexuan
Liu, Qian
Yang, Chaowei
Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method
title Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method
title_full Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method
title_fullStr Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method
title_full_unstemmed Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method
title_short Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method
title_sort public opinions on covid-19 vaccines—a spatiotemporal perspective on races and topics using a bayesian-based method
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504395/
https://www.ncbi.nlm.nih.gov/pubmed/36146564
http://dx.doi.org/10.3390/vaccines10091486
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