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Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak


  • Cynthia Chew
  • Gunther Eysenbach


Background: 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. Methodology/Principal Findings: 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% (R2 = .788; p

Suggested Citation

  • Cynthia Chew & Gunther Eysenbach, 2010. "Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
  • Handle: RePEc:plo:pone00:0014118
    DOI: 10.1371/journal.pone.0014118

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    References listed on IDEAS

    1. Roger E. Kasperson & Ortwin Renn & Paul Slovic & Halina S. Brown & Jacque Emel & Robert Goble & Jeanne X. Kasperson & Samuel Ratick, 1988. "The Social Amplification of Risk: A Conceptual Framework," Risk Analysis, John Wiley & Sons, vol. 8(2), pages 177-187, June.
    2. James Holland Jones & Marcel Salathé, 2009. "Early Assessment of Anxiety and Behavioral Response to Novel Swine-Origin Influenza A(H1N1)," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-8, December.
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    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Swine Influenza (H1N1)


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    Cited by:

    1. Jiayin Pei & Guang Yu & Xianyun Tian & Maureen Renee Donnelley, 2017. "A new method for early detection of mass concern about public health issues," Journal of Risk Research, Taylor & Francis Journals, vol. 20(4), pages 516-532, April.
    2. Zeynep Ertem & Dorrie Raymond & Lauren Ancel Meyers, 2018. "Optimal multi-source forecasting of seasonal influenza," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-16, September.
    3. Krzysztof Janc, 2015. "Visibility and Connections among Cities in Digital Space," Journal of Urban Technology, Taylor & Francis Journals, vol. 22(4), pages 3-21, October.
    4. Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020. "Happiness-lost: Did Governments make the right decisions to combat Covid-19?," GLO Discussion Paper Series 556, Global Labor Organization (GLO).

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