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Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics

There is a compelling and pressing need to better understand the temporal dynamics of public sentiment towards COVID-19 vaccines in the US on a national and state-wise level for facilitating appropriate public policy applications. Our analysis of social media data from early February and late March...

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Autores principales: Ali, G. G. Md. Nawaz, Rahman, Md. Mokhlesur, Hossain, Md. Amjad, Rahman, Md. Shahinoor, Paul, Kamal Chandra, Thill, Jean-Claude, Samuel, Jim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8465389/
https://www.ncbi.nlm.nih.gov/pubmed/34574884
http://dx.doi.org/10.3390/healthcare9091110
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author Ali, G. G. Md. Nawaz
Rahman, Md. Mokhlesur
Hossain, Md. Amjad
Rahman, Md. Shahinoor
Paul, Kamal Chandra
Thill, Jean-Claude
Samuel, Jim
author_facet Ali, G. G. Md. Nawaz
Rahman, Md. Mokhlesur
Hossain, Md. Amjad
Rahman, Md. Shahinoor
Paul, Kamal Chandra
Thill, Jean-Claude
Samuel, Jim
author_sort Ali, G. G. Md. Nawaz
collection PubMed
description There is a compelling and pressing need to better understand the temporal dynamics of public sentiment towards COVID-19 vaccines in the US on a national and state-wise level for facilitating appropriate public policy applications. Our analysis of social media data from early February and late March 2021 shows that, despite the overall strength of positive sentiment and despite the increasing numbers of Americans being fully vaccinated, negative sentiment towards COVID-19 vaccines still persists among segments of people who are hesitant towards the vaccine. In this study, we perform sentiment analytics on vaccine tweets, monitor changes in public sentiment over time, contrast vaccination sentiment scores with actual vaccination data from the US CDC and the Household Pulse Survey (HPS), explore the influence of maturity of Twitter user-accounts and generate geographic mapping of tweet sentiments. We observe that fear sentiment remained unchanged in populous states, whereas trust sentiment declined slightly in these same states. Changes in sentiments were more notable among less populous states in the central sections of the US. Furthermore, we leverage the emotion polarity based Public Sentiment Scenarios (PSS) framework, which was developed for COVID-19 sentiment analytics, to systematically posit implications for public policy processes with the aim of improving the positioning, messaging, and administration of vaccines. These insights are expected to contribute to policies that can expedite the vaccination program and move the nation closer to the cherished herd immunity goal.
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spelling pubmed-84653892021-09-27 Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics Ali, G. G. Md. Nawaz Rahman, Md. Mokhlesur Hossain, Md. Amjad Rahman, Md. Shahinoor Paul, Kamal Chandra Thill, Jean-Claude Samuel, Jim Healthcare (Basel) Article There is a compelling and pressing need to better understand the temporal dynamics of public sentiment towards COVID-19 vaccines in the US on a national and state-wise level for facilitating appropriate public policy applications. Our analysis of social media data from early February and late March 2021 shows that, despite the overall strength of positive sentiment and despite the increasing numbers of Americans being fully vaccinated, negative sentiment towards COVID-19 vaccines still persists among segments of people who are hesitant towards the vaccine. In this study, we perform sentiment analytics on vaccine tweets, monitor changes in public sentiment over time, contrast vaccination sentiment scores with actual vaccination data from the US CDC and the Household Pulse Survey (HPS), explore the influence of maturity of Twitter user-accounts and generate geographic mapping of tweet sentiments. We observe that fear sentiment remained unchanged in populous states, whereas trust sentiment declined slightly in these same states. Changes in sentiments were more notable among less populous states in the central sections of the US. Furthermore, we leverage the emotion polarity based Public Sentiment Scenarios (PSS) framework, which was developed for COVID-19 sentiment analytics, to systematically posit implications for public policy processes with the aim of improving the positioning, messaging, and administration of vaccines. These insights are expected to contribute to policies that can expedite the vaccination program and move the nation closer to the cherished herd immunity goal. MDPI 2021-08-27 /pmc/articles/PMC8465389/ /pubmed/34574884 http://dx.doi.org/10.3390/healthcare9091110 Text en © 2021 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
Ali, G. G. Md. Nawaz
Rahman, Md. Mokhlesur
Hossain, Md. Amjad
Rahman, Md. Shahinoor
Paul, Kamal Chandra
Thill, Jean-Claude
Samuel, Jim
Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics
title Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics
title_full Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics
title_fullStr Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics
title_full_unstemmed Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics
title_short Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics
title_sort public perceptions of covid-19 vaccines: policy implications from us spatiotemporal sentiment analytics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8465389/
https://www.ncbi.nlm.nih.gov/pubmed/34574884
http://dx.doi.org/10.3390/healthcare9091110
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