Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.

Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary "infoveillance" approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms "H1N1"...

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Main Authors: Cynthia Chew, Gunther Eysenbach
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-11-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC2993925?pdf=render
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spelling doaj-1db5e2eab06f41eaa654728349d8c31b2020-11-25T01:52:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-11-01511e1411810.1371/journal.pone.0014118Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.Cynthia ChewGunther EysenbachSurveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary "infoveillance" approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms "H1N1" versus "swine flu" over time; 2) conduct a content analysis of "tweets"; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool.Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords "swine flu," "swineflu," and/or "H1N1." using Infovigil, an infoveillance system. Tweets using "H1N1" increased from 8.8% to 40.5% (R(2) = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data.This study illustrates the potential of using social media to conduct "infodemiology" studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.http://europepmc.org/articles/PMC2993925?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Cynthia Chew
Gunther Eysenbach
spellingShingle Cynthia Chew
Gunther Eysenbach
Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
PLoS ONE
author_facet Cynthia Chew
Gunther Eysenbach
author_sort Cynthia Chew
title Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
title_short Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
title_full Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
title_fullStr Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
title_full_unstemmed Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.
title_sort pandemics in the age of twitter: content analysis of tweets during the 2009 h1n1 outbreak.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2010-11-01
description Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary "infoveillance" approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms "H1N1" versus "swine flu" over time; 2) conduct a content analysis of "tweets"; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool.Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords "swine flu," "swineflu," and/or "H1N1." using Infovigil, an infoveillance system. Tweets using "H1N1" increased from 8.8% to 40.5% (R(2) = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data.This study illustrates the potential of using social media to conduct "infodemiology" studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.
url http://europepmc.org/articles/PMC2993925?pdf=render
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