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Zika discourse in the Americas: A multilingual topic analysis of Twitter

This work examines Twitter discussion surrounding the 2015 outbreak of Zika, a virus that is most often mild but has been associated with serious birth defects and neurological syndromes. We introduce and analyze a collection of 3.9 million tweets mentioning Zika geolocated to North and South Americ...

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Detalles Bibliográficos
Autores principales: Pruss, Dasha, Fujinuma, Yoshinari, Daughton, Ashlynn R., Paul, Michael J., Arnot, Brad, Albers Szafir, Danielle, Boyd-Graber, Jordan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532961/
https://www.ncbi.nlm.nih.gov/pubmed/31120935
http://dx.doi.org/10.1371/journal.pone.0216922
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author Pruss, Dasha
Fujinuma, Yoshinari
Daughton, Ashlynn R.
Paul, Michael J.
Arnot, Brad
Albers Szafir, Danielle
Boyd-Graber, Jordan
author_facet Pruss, Dasha
Fujinuma, Yoshinari
Daughton, Ashlynn R.
Paul, Michael J.
Arnot, Brad
Albers Szafir, Danielle
Boyd-Graber, Jordan
author_sort Pruss, Dasha
collection PubMed
description This work examines Twitter discussion surrounding the 2015 outbreak of Zika, a virus that is most often mild but has been associated with serious birth defects and neurological syndromes. We introduce and analyze a collection of 3.9 million tweets mentioning Zika geolocated to North and South America, where the virus is most prevalent. Using a multilingual topic model, we automatically identify and extract the key topics of discussion across the dataset in English, Spanish, and Portuguese. We examine the variation in Twitter activity across time and location, finding that rises in activity tend to follow to major events, and geographic rates of Zika-related discussion are moderately correlated with Zika incidence (ρ = .398).
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spelling pubmed-65329612019-06-05 Zika discourse in the Americas: A multilingual topic analysis of Twitter Pruss, Dasha Fujinuma, Yoshinari Daughton, Ashlynn R. Paul, Michael J. Arnot, Brad Albers Szafir, Danielle Boyd-Graber, Jordan PLoS One Research Article This work examines Twitter discussion surrounding the 2015 outbreak of Zika, a virus that is most often mild but has been associated with serious birth defects and neurological syndromes. We introduce and analyze a collection of 3.9 million tweets mentioning Zika geolocated to North and South America, where the virus is most prevalent. Using a multilingual topic model, we automatically identify and extract the key topics of discussion across the dataset in English, Spanish, and Portuguese. We examine the variation in Twitter activity across time and location, finding that rises in activity tend to follow to major events, and geographic rates of Zika-related discussion are moderately correlated with Zika incidence (ρ = .398). Public Library of Science 2019-05-23 /pmc/articles/PMC6532961/ /pubmed/31120935 http://dx.doi.org/10.1371/journal.pone.0216922 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Pruss, Dasha
Fujinuma, Yoshinari
Daughton, Ashlynn R.
Paul, Michael J.
Arnot, Brad
Albers Szafir, Danielle
Boyd-Graber, Jordan
Zika discourse in the Americas: A multilingual topic analysis of Twitter
title Zika discourse in the Americas: A multilingual topic analysis of Twitter
title_full Zika discourse in the Americas: A multilingual topic analysis of Twitter
title_fullStr Zika discourse in the Americas: A multilingual topic analysis of Twitter
title_full_unstemmed Zika discourse in the Americas: A multilingual topic analysis of Twitter
title_short Zika discourse in the Americas: A multilingual topic analysis of Twitter
title_sort zika discourse in the americas: a multilingual topic analysis of twitter
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532961/
https://www.ncbi.nlm.nih.gov/pubmed/31120935
http://dx.doi.org/10.1371/journal.pone.0216922
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