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

Abstract

Article Authors Metrics Comments Media Coverage Abstract Introduction Materials and methods Results Discussion Acknowledgments References Reader Comments (0) Media Coverage (0) Figures Abstract 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).

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [3];  [3];  [3];  [3];  [4]
  1. Univ. of Pittsburgh, PA (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. Univ. of Colorado, Boulder, CO (United States)
  4. Univ. of Maryland, College Park, MD (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1526952
Report Number(s):
LA-UR-18-25885
Journal ID: ISSN 1932-6203
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 14; Journal Issue: 5; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; Biological Science; Information Science

Citation Formats

Pruss, Dasha, Daughton, Ashlynn Rae, Paul, Michael J., Fujinuma, Yoshinari, Arnot, Brad, Szafir, Danielle Albers, and Boyd-Graber, Jordan. Zika discourse in the Americas: A multilingual topic analysis of Twitter. United States: N. p., 2019. Web. doi:10.1371/journal.pone.0216922.
Pruss, Dasha, Daughton, Ashlynn Rae, Paul, Michael J., Fujinuma, Yoshinari, Arnot, Brad, Szafir, Danielle Albers, & Boyd-Graber, Jordan. Zika discourse in the Americas: A multilingual topic analysis of Twitter. United States. doi:10.1371/journal.pone.0216922.
Pruss, Dasha, Daughton, Ashlynn Rae, Paul, Michael J., Fujinuma, Yoshinari, Arnot, Brad, Szafir, Danielle Albers, and Boyd-Graber, Jordan. Thu . "Zika discourse in the Americas: A multilingual topic analysis of Twitter". United States. doi:10.1371/journal.pone.0216922. https://www.osti.gov/servlets/purl/1526952.
@article{osti_1526952,
title = {Zika discourse in the Americas: A multilingual topic analysis of Twitter},
author = {Pruss, Dasha and Daughton, Ashlynn Rae and Paul, Michael J. and Fujinuma, Yoshinari and Arnot, Brad and Szafir, Danielle Albers and Boyd-Graber, Jordan},
abstractNote = {Article Authors Metrics Comments Media Coverage Abstract Introduction Materials and methods Results Discussion Acknowledgments References Reader Comments (0) Media Coverage (0) Figures Abstract 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).},
doi = {10.1371/journal.pone.0216922},
journal = {PLoS ONE},
number = 5,
volume = 14,
place = {United States},
year = {2019},
month = {5}
}

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