@Article{Coscia2018,
author="Coscia, Michele
and Hamaguchi, Katsumasa
and Pinglo, Maria Elena
and Giuffrida, Antonio",
title="Mapping the international health aid community using web data",
journal="EPJ Data Science",
year="2018",
month="May",
day="08",
volume="7",
number="1",
pages="12",
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.",
issn="2193-1127",
doi="10.1140/epjds/s13688-018-0141-0",
url="https://doi.org/10.1140/epjds/s13688-018-0141-0"
}