Uncovering Networks of Corporate Control

This project considered corporate networks that model the connectedness of organizations across the globe. It is well-known that firms are not individualistic market actors but instead are embedded in complex networks of corporate control. Analyzing these networks at scale, considering the global economy, its millions of firms and the diverse connections between these firms, requires numerous nontrivial data processing steps, presenting various eScience challenges. An understanding of this data is very much worthwhile for domain experts as it may provide insights in important topics in the socio-economics, such as business elite transnationalization, global cities and offshore financial centers. In this project we looked at the FAIR data principles, as well as two approaches for understanding this data over time, i.e., the longitudinal aspect. One based on the generative models, the other based on understanding changes in the communities in these networks. This lead to both methodological and substantive insights relevant in social network analysis, corporate governance and computational social science in general.