Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017

Detalhes bibliográficos
Autor(a) principal: Araujo, Gabriela Denise de
Data de Publicação: 2020
Outros Autores: Moraes, Fabricio Landi de, Pisa, Ivan Torres
Tipo de documento: Artigo
Idioma: por
Título da fonte: Brazilian Journal of Information Science
Texto Completo: https://revistas.marilia.unesp.br/index.php/bjis/article/view/10179
Resumo: This paper presents a detailed analysis of how health information was shared and discussed on Twitter in terms of awareness and opinions during the 2017 Yellow Fever outbreak in Brazil. For this, the data mining approach with exploratory graph analysis was performed. As main results, Twitter activity peaks were identified compared to peaks of cases reported in some regions of the country, an analysis of hashtags linked to the main subject and different topics from the exploratory analysis of graphs such as vaccination campaign, feelings, prevention, rumors, other diseases linked to the same transmitter, among others. This study illustrates that social networks, such as Twitter, offer unique opportunities for participatory surveillance, which can assist in monitoring some aspects of public health and offer additional data to health managers on how people interact during an outbreak.
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spelling Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017Análisis exploratorio de datos de Twitter: Comprender las conexiones de información de salud durante el brote de fiebre amarilla en 2017Análise exploratória de dados do Twitter: compreendendo as conexões da informação de saúde durante o surto da febre amarela em 2017Redes SociaisMineração de DadosFebre AmarelaAnálise Exploratória de GrafosRedes socialesProcesamiento de datosFiebre amarillaAnálisis Exploratorio de GráficosSocial NetworkData MiningYellow FeverExploratory Graph AnalysisThis paper presents a detailed analysis of how health information was shared and discussed on Twitter in terms of awareness and opinions during the 2017 Yellow Fever outbreak in Brazil. For this, the data mining approach with exploratory graph analysis was performed. As main results, Twitter activity peaks were identified compared to peaks of cases reported in some regions of the country, an analysis of hashtags linked to the main subject and different topics from the exploratory analysis of graphs such as vaccination campaign, feelings, prevention, rumors, other diseases linked to the same transmitter, among others. This study illustrates that social networks, such as Twitter, offer unique opportunities for participatory surveillance, which can assist in monitoring some aspects of public health and offer additional data to health managers on how people interact during an outbreak.Este artículo presenta un análisis exploratorio de cómo se compartió y discutió la información de salud en Twitter en términos de temas de conciencia y posiciones durante el brote de fiebre amarilla de 2017 en Brasil. Para esto, se utilizó el enfoque de minería de datos con análisis de gráficos exploratorios. Como resultados principales, se identificaron picos de mensajes en comparación con los picos de casos reportados en algunas regiones del país, un análisis de hashtags vinculados al tema principal y diferentes temas del análisis exploratorio de gráficos como campaña de vacunación, sentimientos, prevención, rumores, otras enfermedades vinculadas al mismo transmisor, entre otras. Este estudio demostró que las redes sociales, como Twitter, ofrecen oportunidades únicas para la vigilancia participativa, que puede ayudar a monitorear algunos aspectos de la salud pública y ofrecer datos adicionales a los administradores de salud sobre cómo las personas interactúan durante un brote.Este artigo apresenta uma análise exploratória de como as informações de saúde foram compartilhadas e discutidas no Twitter em termos de tópicos de conscientização e posicionamentos durante surto da Febre Amarela de 2017 no Brasil. Para isso, foi utilizada a abordagem de mineração de dados com análise exploratória de grafos. Como principais resultados, foram identificados os picos de mensagens comparados aos picos de casos notificados em algumas regiões do país, uma análise das hashtags vinculadas ao principal assunto e diferentes tópicos oriundos da análise exploratória de grafos como campanha de vacinação, sentimentos, prevenção, rumores, outras doenças vinculadas ao mesmo transmissor entre outros. Este estudo demonstrou que as redes sociais, como o Twitter, oferecem oportunidades únicas para a vigilância participativa, podendo auxiliar no monitoramento de alguns aspectos da saúde pública e oferecer dados adicionais aos gestores de saúde de como as pessoas interagem durante um surto.Faculdade de Filosofia e Ciências2020-08-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.marilia.unesp.br/index.php/bjis/article/view/1017910.36311/1940-1640.2020.v14n3.10179Brazilian Journal of Information Science: Research Trends; Vol. 14 No. 3 - jul-set (2020); e020006Brazilian Journal of Information Science: Research Trends; Vol. 14 Núm. 3 - jul-set (2020); e020006Brazilian Journal of Information Science: research trends; v. 14 n. 3 - jul-set (2020); e0200061981-1640reponame:Brazilian Journal of Information Scienceinstname:Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)instacron:UNESPporhttps://revistas.marilia.unesp.br/index.php/bjis/article/view/10179/6731Copyright (c) 2020 Gabriela Denise de Araujo, Fabricio Landi de Moraes, Ivan Torres Pisainfo:eu-repo/semantics/openAccessAraujo, Gabriela Denise deMoraes, Fabricio Landi dePisa, Ivan Torres2022-01-04T19:40:50Zoai:ojs.www2.marilia.unesp.br:article/10179Revistahttps://revistas.marilia.unesp.br/index.php/bjis/indexPUBhttps://revistas.marilia.unesp.br/index.php/bjis/oaibrajis.marilia@unesp.br||1981-16401981-1640opendoar:2022-01-04T19:40:50Brazilian Journal of Information Science - Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)false
dc.title.none.fl_str_mv Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
Análisis exploratorio de datos de Twitter: Comprender las conexiones de información de salud durante el brote de fiebre amarilla en 2017
Análise exploratória de dados do Twitter: compreendendo as conexões da informação de saúde durante o surto da febre amarela em 2017
title Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
spellingShingle Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
Araujo, Gabriela Denise de
Redes Sociais
Mineração de Dados
Febre Amarela
Análise Exploratória de Grafos
Redes sociales
Procesamiento de datos
Fiebre amarilla
Análisis Exploratorio de Gráficos
Social Network
Data Mining
Yellow Fever
Exploratory Graph Analysis
title_short Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
title_full Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
title_fullStr Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
title_full_unstemmed Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
title_sort Exploratory Analysis of Twitter data: Understanding the health information connections during the Yellow Fever Outbreak in 2017
author Araujo, Gabriela Denise de
author_facet Araujo, Gabriela Denise de
Moraes, Fabricio Landi de
Pisa, Ivan Torres
author_role author
author2 Moraes, Fabricio Landi de
Pisa, Ivan Torres
author2_role author
author
dc.contributor.author.fl_str_mv Araujo, Gabriela Denise de
Moraes, Fabricio Landi de
Pisa, Ivan Torres
dc.subject.por.fl_str_mv Redes Sociais
Mineração de Dados
Febre Amarela
Análise Exploratória de Grafos
Redes sociales
Procesamiento de datos
Fiebre amarilla
Análisis Exploratorio de Gráficos
Social Network
Data Mining
Yellow Fever
Exploratory Graph Analysis
topic Redes Sociais
Mineração de Dados
Febre Amarela
Análise Exploratória de Grafos
Redes sociales
Procesamiento de datos
Fiebre amarilla
Análisis Exploratorio de Gráficos
Social Network
Data Mining
Yellow Fever
Exploratory Graph Analysis
description This paper presents a detailed analysis of how health information was shared and discussed on Twitter in terms of awareness and opinions during the 2017 Yellow Fever outbreak in Brazil. For this, the data mining approach with exploratory graph analysis was performed. As main results, Twitter activity peaks were identified compared to peaks of cases reported in some regions of the country, an analysis of hashtags linked to the main subject and different topics from the exploratory analysis of graphs such as vaccination campaign, feelings, prevention, rumors, other diseases linked to the same transmitter, among others. This study illustrates that social networks, such as Twitter, offer unique opportunities for participatory surveillance, which can assist in monitoring some aspects of public health and offer additional data to health managers on how people interact during an outbreak.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-28
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistas.marilia.unesp.br/index.php/bjis/article/view/10179
10.36311/1940-1640.2020.v14n3.10179
url https://revistas.marilia.unesp.br/index.php/bjis/article/view/10179
identifier_str_mv 10.36311/1940-1640.2020.v14n3.10179
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://revistas.marilia.unesp.br/index.php/bjis/article/view/10179/6731
dc.rights.driver.fl_str_mv Copyright (c) 2020 Gabriela Denise de Araujo, Fabricio Landi de Moraes, Ivan Torres Pisa
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Gabriela Denise de Araujo, Fabricio Landi de Moraes, Ivan Torres Pisa
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Faculdade de Filosofia e Ciências
publisher.none.fl_str_mv Faculdade de Filosofia e Ciências
dc.source.none.fl_str_mv Brazilian Journal of Information Science: Research Trends; Vol. 14 No. 3 - jul-set (2020); e020006
Brazilian Journal of Information Science: Research Trends; Vol. 14 Núm. 3 - jul-set (2020); e020006
Brazilian Journal of Information Science: research trends; v. 14 n. 3 - jul-set (2020); e020006
1981-1640
reponame:Brazilian Journal of Information Science
instname:Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Brazilian Journal of Information Science
collection Brazilian Journal of Information Science
repository.name.fl_str_mv Brazilian Journal of Information Science - Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)
repository.mail.fl_str_mv brajis.marilia@unesp.br||
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