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Conceptualizing an Ecological Model of Google Search and Twitter Data in Public Health

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Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics

Part of the book series: Human Dynamics in Smart Cities ((HDSC))

Abstract

More and more Internet users are engaging in health-related online activities such as online search for health information or sharing experience in online communities. Geo-tagged and time-stamped data generated from these online activities could inform public health practitioners of the population’s information needs, opinions, attitudes, and behaviors on specific health issues, and health status, becoming an important source of public health surveillance. The heterogeneity and multi-facet nature of social media and search data requires an ecological view to guide big data analysis, interpretation, and visualization. In our work, we recognize the complexity and dynamics of big data, and the efforts of previous scholars in collecting, cleaning/filtering, analyzing, and modeling big data—especially, Google search and Twitter data for public health surveillance. Through eight propositions, we construct an ecological model of Google Search and Twitter data for public health surveillance by differentiating message sources, goals, content, and geo- and time-stamped information. This model monitors public attention of health issues by analyzing information flow from celebrities, media, organizations, blogs, to consumers, who react, by retweeting or searching online. In addition, it detects diseases by examining consumers’ reports of personal experiences on Twitter and online search.

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Authors and Affiliations

  1. Department of Business, Nevada State College, Henderson, NV, USA

    Bo Liang

  2. College of Arts and Sciences, University of Missouri – Kansas City, Kansas City, MO, USA

    Ye Wang

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  1. Bo Liang
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Correspondence to Bo Liang .

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Editors and Affiliations

  1. Department of Geography, San Diego State University, San Diego, CA, USA

    Atsushi Nara

  2. Department of Geography, San Diego State University, San Diego, CA, USA

    Ming-Hsiang Tsou

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Liang, B., Wang, Y. (2021). Conceptualizing an Ecological Model of Google Search and Twitter Data in Public Health. In: Nara, A., Tsou, MH. (eds) Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics. Human Dynamics in Smart Cities. Springer, Cham. https://doi.org/10.1007/978-3-030-83010-6_10

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