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Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019

Vaccine hesitancy was one of the ten major threats to global health in 2019, according to the World Health Organisation. Nowadays, social media has an important role in the spread of information, misinformation, and disinformation about vaccines. Monitoring vaccine-related conversations on social me...

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Autores principales: Piedrahita-Valdés, Hilary, Piedrahita-Castillo, Diego, Bermejo-Higuera, Javier, Guillem-Saiz, Patricia, Bermejo-Higuera, Juan Ramón, Guillem-Saiz, Javier, Sicilia-Montalvo, Juan Antonio, Machío-Regidor, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7827575/
https://www.ncbi.nlm.nih.gov/pubmed/33430428
http://dx.doi.org/10.3390/vaccines9010028
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author Piedrahita-Valdés, Hilary
Piedrahita-Castillo, Diego
Bermejo-Higuera, Javier
Guillem-Saiz, Patricia
Bermejo-Higuera, Juan Ramón
Guillem-Saiz, Javier
Sicilia-Montalvo, Juan Antonio
Machío-Regidor, Francisco
author_facet Piedrahita-Valdés, Hilary
Piedrahita-Castillo, Diego
Bermejo-Higuera, Javier
Guillem-Saiz, Patricia
Bermejo-Higuera, Juan Ramón
Guillem-Saiz, Javier
Sicilia-Montalvo, Juan Antonio
Machío-Regidor, Francisco
author_sort Piedrahita-Valdés, Hilary
collection PubMed
description Vaccine hesitancy was one of the ten major threats to global health in 2019, according to the World Health Organisation. Nowadays, social media has an important role in the spread of information, misinformation, and disinformation about vaccines. Monitoring vaccine-related conversations on social media could help us to identify the factors that contribute to vaccine confidence in each historical period and geographical area. We used a hybrid approach to perform an opinion-mining analysis on 1,499,227 vaccine-related tweets published on Twitter from 1st June 2011 to 30th April 2019. Our algorithm classified 69.36% of the tweets as neutral, 21.78% as positive, and 8.86% as negative. The percentage of neutral tweets showed a decreasing tendency, while the proportion of positive and negative tweets increased over time. Peaks in positive tweets were observed every April. The proportion of positive tweets was significantly higher in the middle of the week and decreased during weekends. Negative tweets followed the opposite pattern. Among users with ≥2 tweets, 91.83% had a homogeneous polarised discourse. Positive tweets were more prevalent in Switzerland (71.43%). Negative tweets were most common in the Netherlands (15.53%), Canada (11.32%), Japan (10.74%), and the United States (10.49%). Opinion mining is potentially useful to monitor online vaccine-related concerns and adapt vaccine promotion strategies accordingly.
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spelling pubmed-78275752021-01-25 Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019 Piedrahita-Valdés, Hilary Piedrahita-Castillo, Diego Bermejo-Higuera, Javier Guillem-Saiz, Patricia Bermejo-Higuera, Juan Ramón Guillem-Saiz, Javier Sicilia-Montalvo, Juan Antonio Machío-Regidor, Francisco Vaccines (Basel) Article Vaccine hesitancy was one of the ten major threats to global health in 2019, according to the World Health Organisation. Nowadays, social media has an important role in the spread of information, misinformation, and disinformation about vaccines. Monitoring vaccine-related conversations on social media could help us to identify the factors that contribute to vaccine confidence in each historical period and geographical area. We used a hybrid approach to perform an opinion-mining analysis on 1,499,227 vaccine-related tweets published on Twitter from 1st June 2011 to 30th April 2019. Our algorithm classified 69.36% of the tweets as neutral, 21.78% as positive, and 8.86% as negative. The percentage of neutral tweets showed a decreasing tendency, while the proportion of positive and negative tweets increased over time. Peaks in positive tweets were observed every April. The proportion of positive tweets was significantly higher in the middle of the week and decreased during weekends. Negative tweets followed the opposite pattern. Among users with ≥2 tweets, 91.83% had a homogeneous polarised discourse. Positive tweets were more prevalent in Switzerland (71.43%). Negative tweets were most common in the Netherlands (15.53%), Canada (11.32%), Japan (10.74%), and the United States (10.49%). Opinion mining is potentially useful to monitor online vaccine-related concerns and adapt vaccine promotion strategies accordingly. MDPI 2021-01-07 /pmc/articles/PMC7827575/ /pubmed/33430428 http://dx.doi.org/10.3390/vaccines9010028 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Piedrahita-Valdés, Hilary
Piedrahita-Castillo, Diego
Bermejo-Higuera, Javier
Guillem-Saiz, Patricia
Bermejo-Higuera, Juan Ramón
Guillem-Saiz, Javier
Sicilia-Montalvo, Juan Antonio
Machío-Regidor, Francisco
Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019
title Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019
title_full Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019
title_fullStr Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019
title_full_unstemmed Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019
title_short Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019
title_sort vaccine hesitancy on social media: sentiment analysis from june 2011 to april 2019
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7827575/
https://www.ncbi.nlm.nih.gov/pubmed/33430428
http://dx.doi.org/10.3390/vaccines9010028
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