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The Global Health Networks: A Comparative Analysis of Tuberculosis, Malaria and Pneumonia Using Social Media Data

Author

Listed:
  • Milena Lopreite

    (Scuola Superiore Sant’Anna)

  • Michelangelo Puliga

    (IMT School for Advanced Studies Lucca)

  • Massimo Riccaboni

    (IMT School for Advanced Studies Lucca)

Abstract

Global health networks (GHNs) of organizations fighting major health threats represent a useful strategy to respond to the challenge of mobilizing and coordinating different types of health organizations across borders toward a common goal. In this paper we reconstruct the GHNs of malaria, tuberculosis and pneumonia by creating a new unique database of health organizations from the official Twitter accounts of each organization. We use a majority voter Multi Naive Bayes classifier to discover, among the Twitter users, the ones that represent organizations or groups active in each disease area. We perform a social network analysis (SNA) of the global health networks (GHNs) to evaluate the structure of the network and the role and performance of the organizations in each network. We find evidence that the GHN of malaria, TBC and pneumonia are different in terms of performance and leadership, geographical coverage as well as Twitter popularity. Our analysis validate the use of social media to analyze GHNs, their effectiveness and to mobilize the global community toward global sustainable development.

Suggested Citation

  • Milena Lopreite & Michelangelo Puliga & Massimo Riccaboni, 2018. "The Global Health Networks: A Comparative Analysis of Tuberculosis, Malaria and Pneumonia Using Social Media Data," Working Papers 01/2018, IMT School for Advanced Studies Lucca, revised Jan 2018.
    • Handle: RePEc:ial:wpaper:1/2018
    as

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    File URL: http://eprints.imtlucca.it/3856/1/EIC_WP_2018_1.pdf
    File Function: First version, 2018
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    References listed on IDEAS

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    Cited by:

    1. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.

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    More about this item

    Keywords

    global health network; social network analysis; machine learning classifier; tuberculosis; malaria; pneumonia; policy evaluation;
    All these keywords.

    JEL classification:

    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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