Cargando…
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...
Autores principales: | , , , , , , , , , , |
---|---|
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 |
_version_ | 1784796205048397824 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9504395 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wangzifu publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT chenyudi publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT liyun publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT kakkardevika publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT guanwendy publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT jiwenying publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT cainjacob publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT lanhai publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT shadexuan publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT liuqian publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod AT yangchaowei publicopinionsoncovid19vaccinesaspatiotemporalperspectiveonracesandtopicsusingabayesianbasedmethod |