Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy

Public health; Social networking (online); Vaccines; Coronaviruses; Medical; Multi-perspective; Scientific discipline; Sentiment analysis; Social; Social media; Systematic Review; Technology; Vaccine hesitancy; Sentiment analysis; Human papilloma virus vaccine; measles vaccine; SARS-CoV-2 vaccine; a...

Full description

Saved in:

Bibliographic Details
Main Authors:	Alamoodi A.H., Zaidan B.B., Al-Masawa M., Taresh S.M., Noman S., Ahmaro I.Y.Y., Garfan S., Chen J., Ahmed M.A., Zaidan A.A., Albahri O.S., Aickelin U., Thamir N.N., Fadhil J.A., Salahaldin A.
Other Authors:	57205435311
Format:	Review
Published:	Elsevier Ltd 2023
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Universiti Tenaga Nasional

id	my.uniten.dspace-25873
record_format	dspace
spelling	my.uniten.dspace-258732023-05-29T17:05:22Z Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy Alamoodi A.H. Zaidan B.B. Al-Masawa M. Taresh S.M. Noman S. Ahmaro I.Y.Y. Garfan S. Chen J. Ahmed M.A. Zaidan A.A. Albahri O.S. Aickelin U. Thamir N.N. Fadhil J.A. Salahaldin A. 57205435311 35070872100 57219935987 57216158622 57214938634 56644806700 57213826607 57189597579 57763079000 35070838500 57201013684 11339382200 57226713718 57221314303 57313094100 Public health; Social networking (online); Vaccines; Coronaviruses; Medical; Multi-perspective; Scientific discipline; Sentiment analysis; Social; Social media; Systematic Review; Technology; Vaccine hesitancy; Sentiment analysis; Human papilloma virus vaccine; measles vaccine; SARS-CoV-2 vaccine; artificial intelligence; conspiracy theory; contact examination; coronavirus disease 2019; deep learning; health promotion; human; machine learning; measles; medical technology; misinformation; natural language processing; pandemic; papillomavirus infection; population surveillance; public health message; public opinion; Review; sentiment analysis; social media; statistical analysis; systematic review; transfer of learning; vaccination; vaccination coverage; vaccine hesitancy; COVID-19; COVID-19 Vaccines; Humans; SARS-CoV-2; Sentiment Analysis; Vaccination; Vaccination Hesitancy A substantial impediment to widespread Coronavirus disease (COVID-19) vaccination is vaccine hesitancy. Many researchers across scientific disciplines have presented countless studies in favor of COVID-19 vaccination, but misinformation on social media could hinder vaccination efforts and increase vaccine hesitancy. Nevertheless, studying people's perceptions on social media to understand their sentiment presents a powerful medium for researchers to identify the causes of vaccine hesitancy and therefore develop appropriate public health messages and interventions. To the best of the authors' knowledge, previous studies have presented vaccine hesitancy in specific cases or within one scientific discipline (i.e., social, medical, and technological). No previous study has presented findings via sentiment analysis for multiple scientific disciplines as follows: (1) social, (2) medical, public health, and (3) technology sciences. Therefore, this research aimed to review and analyze articles related to different vaccine hesitancy cases in the last 11 years and understand the application of sentiment analysis on the most important literature findings. Articles were systematically searched in Web of Science, Scopus, PubMed, IEEEXplore, ScienceDirect, and Ovid from January 1, 2010, to July 2021. A total of 30 articles were selected on the basis of inclusion and exclusion criteria. These articles were formed into a taxonomy of literature, along with challenges, motivations, and recommendations for social, medical, and public health and technology sciences. Significant patterns were identified, and opportunities were promoted towards the understanding of this phenomenon. � 2021 Elsevier Ltd Final 2023-05-29T09:05:22Z 2023-05-29T09:05:22Z 2021 Review 10.1016/j.compbiomed.2021.104957 2-s2.0-85117894540 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117894540&doi=10.1016%2fj.compbiomed.2021.104957&partnerID=40&md5=a29948bc226d2b6e7e8df8d09ca06174 https://irepository.uniten.edu.my/handle/123456789/25873 139 104957 All Open Access, Green Elsevier Ltd Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
description	Public health; Social networking (online); Vaccines; Coronaviruses; Medical; Multi-perspective; Scientific discipline; Sentiment analysis; Social; Social media; Systematic Review; Technology; Vaccine hesitancy; Sentiment analysis; Human papilloma virus vaccine; measles vaccine; SARS-CoV-2 vaccine; artificial intelligence; conspiracy theory; contact examination; coronavirus disease 2019; deep learning; health promotion; human; machine learning; measles; medical technology; misinformation; natural language processing; pandemic; papillomavirus infection; population surveillance; public health message; public opinion; Review; sentiment analysis; social media; statistical analysis; systematic review; transfer of learning; vaccination; vaccination coverage; vaccine hesitancy; COVID-19; COVID-19 Vaccines; Humans; SARS-CoV-2; Sentiment Analysis; Vaccination; Vaccination Hesitancy
author2	57205435311
author_facet	57205435311 Alamoodi A.H. Zaidan B.B. Al-Masawa M. Taresh S.M. Noman S. Ahmaro I.Y.Y. Garfan S. Chen J. Ahmed M.A. Zaidan A.A. Albahri O.S. Aickelin U. Thamir N.N. Fadhil J.A. Salahaldin A.
format	Review
author	Alamoodi A.H. Zaidan B.B. Al-Masawa M. Taresh S.M. Noman S. Ahmaro I.Y.Y. Garfan S. Chen J. Ahmed M.A. Zaidan A.A. Albahri O.S. Aickelin U. Thamir N.N. Fadhil J.A. Salahaldin A.
spellingShingle	Alamoodi A.H. Zaidan B.B. Al-Masawa M. Taresh S.M. Noman S. Ahmaro I.Y.Y. Garfan S. Chen J. Ahmed M.A. Zaidan A.A. Albahri O.S. Aickelin U. Thamir N.N. Fadhil J.A. Salahaldin A. Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
author_sort	Alamoodi A.H.
title	Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
title_short	Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
title_full	Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
title_fullStr	Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
title_full_unstemmed	Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
title_sort	multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
publisher	Elsevier Ltd
publishDate	2023
_version_	1806426397573382144

Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy

Similar Items