Coscia, M., et al., 2018. Mapping the International Health Aid Community using Web Data. EPJ Data Science , 7:12. Copy at http://www.tinyurl.com/y3x9j5qb
Abstract:International aid is a complex system: it involves different issues, countries, and donors. In this paper, we use web crawling to collect information about the activities of international aid organizations on different health-related topics and network analysis to depict this complex system of relationships among organizations. By systematically collecting co-occurrences of issues, countries, and organization names from more than a hundred websites, we are able to construct multilayer networks describing, for instance, which issues are related to each other according to which organizations. Our results show that there is a surprising amount of homophily among organizations: organizations of the same type (multilateral, bilateral, private donors, etc.) tend to be co-cited in groups. We also create a taxonomy of issues that are generally mentioned together. Finally, we perform simulations, showing that messages originating from different organizations in the international aid community can have a different reach.
Keywords: Web crawling; Global health architecture; Complex networks