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Perception of COVID-19 vaccination among Indian Twitter users: computational approach

Vaccination has been a hot topic in the present COVID-19 context. The government, public health stakeholders and media are all concerned about how to get the people vaccinated. The study was intended to explore the perception and emotions of the Indians citizens toward COVID-19 vaccine from Twitter...

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Autores principales: Davidson, Prateeksha Dawn, Muniandy, Thanujah, Karmegam, Dhivya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047476/
https://www.ncbi.nlm.nih.gov/pubmed/37363805
http://dx.doi.org/10.1007/s42001-023-00203-0
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author Davidson, Prateeksha Dawn
Muniandy, Thanujah
Karmegam, Dhivya
author_facet Davidson, Prateeksha Dawn
Muniandy, Thanujah
Karmegam, Dhivya
author_sort Davidson, Prateeksha Dawn
collection PubMed
description Vaccination has been a hot topic in the present COVID-19 context. The government, public health stakeholders and media are all concerned about how to get the people vaccinated. The study was intended to explore the perception and emotions of the Indians citizens toward COVID-19 vaccine from Twitter messages. The tweets were collected for the period of 6 months, from mid-January to June, 2021 using hash-tags and keywords specific to India. Topics and emotions from the tweets were extracted using Latent Dirichlet Allocation (LDA) method and National Research Council (NRC) Lexicon, respectively. Theme, sentiment and emotion wise engagement and reachability metrics were assessed. Hash-tag frequency of COVID-19 vaccine brands were also identified and evaluated. Information regarding ‘Co-WIN app and availability of vaccine’ was widely discussed and also received highest engagement and reachability among Twitter users. Among the various emotions, trust was expressed the most, which highlights the acceptance of vaccines among the Indian citizens. The hash-tags frequency of vaccine brands shows that Covishield was popular in the month of March 2021, and Covaxin in April 2021. The results from the study will help stakeholders to efficiently use social media to disseminate COVID-19 vaccine information on popular concerns. This in turn will encourage citizens to be vaccinated and achieve herd immunity. Similar methodology can be adopted in future to understand the perceptions and concerns of people in emergency situations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42001-023-00203-0.
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spelling pubmed-100474762023-03-29 Perception of COVID-19 vaccination among Indian Twitter users: computational approach Davidson, Prateeksha Dawn Muniandy, Thanujah Karmegam, Dhivya J Comput Soc Sci Research Article Vaccination has been a hot topic in the present COVID-19 context. The government, public health stakeholders and media are all concerned about how to get the people vaccinated. The study was intended to explore the perception and emotions of the Indians citizens toward COVID-19 vaccine from Twitter messages. The tweets were collected for the period of 6 months, from mid-January to June, 2021 using hash-tags and keywords specific to India. Topics and emotions from the tweets were extracted using Latent Dirichlet Allocation (LDA) method and National Research Council (NRC) Lexicon, respectively. Theme, sentiment and emotion wise engagement and reachability metrics were assessed. Hash-tag frequency of COVID-19 vaccine brands were also identified and evaluated. Information regarding ‘Co-WIN app and availability of vaccine’ was widely discussed and also received highest engagement and reachability among Twitter users. Among the various emotions, trust was expressed the most, which highlights the acceptance of vaccines among the Indian citizens. The hash-tags frequency of vaccine brands shows that Covishield was popular in the month of March 2021, and Covaxin in April 2021. The results from the study will help stakeholders to efficiently use social media to disseminate COVID-19 vaccine information on popular concerns. This in turn will encourage citizens to be vaccinated and achieve herd immunity. Similar methodology can be adopted in future to understand the perceptions and concerns of people in emergency situations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42001-023-00203-0. Springer Nature Singapore 2023-03-28 /pmc/articles/PMC10047476/ /pubmed/37363805 http://dx.doi.org/10.1007/s42001-023-00203-0 Text en © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Davidson, Prateeksha Dawn
Muniandy, Thanujah
Karmegam, Dhivya
Perception of COVID-19 vaccination among Indian Twitter users: computational approach
title Perception of COVID-19 vaccination among Indian Twitter users: computational approach
title_full Perception of COVID-19 vaccination among Indian Twitter users: computational approach
title_fullStr Perception of COVID-19 vaccination among Indian Twitter users: computational approach
title_full_unstemmed Perception of COVID-19 vaccination among Indian Twitter users: computational approach
title_short Perception of COVID-19 vaccination among Indian Twitter users: computational approach
title_sort perception of covid-19 vaccination among indian twitter users: computational approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047476/
https://www.ncbi.nlm.nih.gov/pubmed/37363805
http://dx.doi.org/10.1007/s42001-023-00203-0
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