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Fear on the networks: analyzing the 2014 Ebola outbreak
During the 2014 Ebola outbreak, information spread via multiple platforms, including social networks and Internet search engines. This report analyzes Twitter tweets, Facebook posts, and Google trends, as well as several other Internet resources, from March – November 2014. Understanding the types o...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Organización Panamericana de la Salud
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645359/ https://www.ncbi.nlm.nih.gov/pubmed/31384264 http://dx.doi.org/10.26633/RPSP.2017.134 |
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author | D´Agostino, Marcelo Mejía, Felipe Brooks, Ian Marti, Myrna Novillo-Ortiz, David de Cosio, Gerardo |
author_facet | D´Agostino, Marcelo Mejía, Felipe Brooks, Ian Marti, Myrna Novillo-Ortiz, David de Cosio, Gerardo |
author_sort | D´Agostino, Marcelo |
collection | PubMed |
description | During the 2014 Ebola outbreak, information spread via multiple platforms, including social networks and Internet search engines. This report analyzes Twitter tweets, Facebook posts, and Google trends, as well as several other Internet resources, from March – November 2014. Understanding the types of discussions, social behaviors, feelings expressed, and information shared during the Ebola outbreak can help health organizations improve communication interventions and avert misinformation and panic during health emergencies. In all, 6 422 170 tweets, 83 Facebook posts, and Google search trends were integrated with 63 chronological Ebola-related events. Events that prompted a surge in tweets using #ebola were related to new cases of infection or the entry of the disease into a new goegraphic area. Most tweets were re-tweets of information provided by news agencies and official health organizations. Events related to new infections and deaths seemed to correlate with an increase of words that express fear. Google results concurred with Twitter and Facebook. Data from social media activity can be used to form hypotheses about how the public responds to and behaves during public health events, prompting health organizations to adopt new strategies for communications interventions. Furthermore, a spike in activity around a topic can be used as a surveillance technique to signal to health authorities that an outbreak may be underway. It is also recommended that news agencies, which engage with the public most often, consider content review by health experts as part of their health communications process. |
format | Online Article Text |
id | pubmed-6645359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Organización Panamericana de la Salud |
record_format | MEDLINE/PubMed |
spelling | pubmed-66453592019-08-05 Fear on the networks: analyzing the 2014 Ebola outbreak D´Agostino, Marcelo Mejía, Felipe Brooks, Ian Marti, Myrna Novillo-Ortiz, David de Cosio, Gerardo Rev Panam Salud Publica Special Report During the 2014 Ebola outbreak, information spread via multiple platforms, including social networks and Internet search engines. This report analyzes Twitter tweets, Facebook posts, and Google trends, as well as several other Internet resources, from March – November 2014. Understanding the types of discussions, social behaviors, feelings expressed, and information shared during the Ebola outbreak can help health organizations improve communication interventions and avert misinformation and panic during health emergencies. In all, 6 422 170 tweets, 83 Facebook posts, and Google search trends were integrated with 63 chronological Ebola-related events. Events that prompted a surge in tweets using #ebola were related to new cases of infection or the entry of the disease into a new goegraphic area. Most tweets were re-tweets of information provided by news agencies and official health organizations. Events related to new infections and deaths seemed to correlate with an increase of words that express fear. Google results concurred with Twitter and Facebook. Data from social media activity can be used to form hypotheses about how the public responds to and behaves during public health events, prompting health organizations to adopt new strategies for communications interventions. Furthermore, a spike in activity around a topic can be used as a surveillance technique to signal to health authorities that an outbreak may be underway. It is also recommended that news agencies, which engage with the public most often, consider content review by health experts as part of their health communications process. Organización Panamericana de la Salud 2017-12-05 /pmc/articles/PMC6645359/ /pubmed/31384264 http://dx.doi.org/10.26633/RPSP.2017.134 Text en https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 IGO License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited. No modifications or commercial use of this article are permitted. In any reproduction of this article there should not be any suggestion that PAHO or this article endorse any specific organization or products. The use of the PAHO logo is not permitted. This notice should be preserved along with the article’s original URL. |
spellingShingle | Special Report D´Agostino, Marcelo Mejía, Felipe Brooks, Ian Marti, Myrna Novillo-Ortiz, David de Cosio, Gerardo Fear on the networks: analyzing the 2014 Ebola outbreak |
title | Fear on the networks: analyzing the 2014 Ebola outbreak |
title_full | Fear on the networks: analyzing the 2014 Ebola outbreak |
title_fullStr | Fear on the networks: analyzing the 2014 Ebola outbreak |
title_full_unstemmed | Fear on the networks: analyzing the 2014 Ebola outbreak |
title_short | Fear on the networks: analyzing the 2014 Ebola outbreak |
title_sort | fear on the networks: analyzing the 2014 ebola outbreak |
topic | Special Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645359/ https://www.ncbi.nlm.nih.gov/pubmed/31384264 http://dx.doi.org/10.26633/RPSP.2017.134 |
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