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

Milena Lopreite (), Michelangelo Puliga () and Massimo Riccaboni ()
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Milena Lopreite: Scuola Superiore Sant’Anna
Michelangelo Puliga: IMT School for Advanced Studies Lucca

No 01/2018, Working Papers from 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.

Keywords: global health network; social network analysis; machine learning classifier; tuberculosis; malaria; pneumonia; policy evaluation (search for similar items in EconPapers)
JEL-codes: C8 I15 I18 (search for similar items in EconPapers)
Pages: 33
Date: 2018-01, Revised 2018-01
New Economics Papers: this item is included in nep-big and nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in EIC working paper series

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http://eprints.imtlucca.it/3856/1/EIC_WP_2018_1.pdf First version, 2018

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