@article {1313740,
	title = {Mapping the International Health Aid Community using Web Data},
	journal = {EPJ Data Science},
	volume = {7:12},
	year = {2018},
	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.},
	url = {https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-018-0141-0},
	author = {Michele Coscia and Katsumasa Hamaguchi and Maria Elena Pinglo and Antonio Giuffrida}
}
