Members of the CORPNET group at the University of Amsterdam

Frank Takes is an assistant professor at Leiden University and member of the CORPNET group at the University of Amsterdam, where he was previously employed as a postdoctoral researcher.

In 2017 Frank won the Young eScientist Award. He received in-kind expertise from the eScience Center for his project Uncovering Networks of Corporate Control, where the goal was to create an interactive web-based platform to investigate the dynamics of global corporate networks.

By collaborating with the eScience Center, Frank and his fellow researchers at UvA CORPNET group aim to better understand the transnational interconnectedness of corporations and how this influences people, organizations and institutions.

The Project: Uncovering Networks of Corporate Control

The multidisciplinary field of computational social science deals with research on computational methods for understanding our highly complex society. The ERC-funded CORPNET research group at the University of Amsterdam is particularly concerned with understanding the global socioeconomic system. More specifically, the aim is to understand the transnational interconnectedness of corporations and how this influences people, organizations and institutions. The work done so far has provided novel insights in topics such as corporate elites, state investment strategies, the detection of tax havens, but for example also the economic connectedness of global cities in what is called a small-world network.

Corporate networks model the connectivity of global business, allowing network science techniques to find meaningful patterns

Novel insights

Apart from addressing social science questions, we advance methods in the field of computational social science and data science, including modeling, simulation, and most importantly, social network analysis. This field, sometimes also called network science, considers modeling data as a network of entities and the interactions between these entities. By doing so, we can discover novel insights in the underlying complex system that would otherwise remain hidden. We particularly aim to do so for large-scale data; in our case a large network dataset of over one hundred million companies and the various social and economic links between these organizations.

Collaboration & Research between different disciplines

The type of research done in our group is highly interdisciplinary. The aim is not to have the computational aspect only support the social sciences, or to merely enrich the methodological work with some societal application domain. Instead, we want to advance both the social sciences as well as computer science and eScience methodologies. This involves working together in teams consisting of people with different mixed disciplines that have a natural drive to understand each other’s goals and objectives.

Netherlands eScience Center research engineers Dafne van Kuppevelt and Laurens Bogaardt joined the CORPNET group in the beginning of 2018 as part of Frank Takes’s eScience pathfinder project Uncovering Networks of Corporate Control. It was a pleasure to collaborate with both of them, as they fully understood the interdisciplinary angle that plays such a central role in our research group.

Frank Takes (University of Amsterdam) and Laurens Bogaardt (Netherlands eScience Center)

“ The first challenge in any collaboration is communication — understanding what the aim of the project should be. Fortunately, with experience, this challenge can be tackled. The main advantage I see in collaborating with a diverse group of people is the jolt it gives to your creativity, leading to new ideas and solution both within the project and in other, future projects.” — Laurens Bogaardt

“The advantages of collaborations are that it is fun and rewarding, when coming from different disciplines you can really complement each other. The challenge is that it takes effort to understand where collaborators are coming from and what the norms in a different field are.” — Dafne van Kuppevelt

Sharing knowledge and tools to drive research forward

The eScience research engineers were able to quickly identify highly relevant scientific problems relevant to our research group where they could employ their expertise.

Laurens worked on methods for dynamic social network analysis for which a theoretical model was proposed, but no efficient implementation yet existed. Using a thorough mathematical analysis, he devised a scalable implementation of this model. In the future, this will allow us to study large-scale dynamic network data, surpassing previous computational limits of these types of models.

Dafne worked on the problem of network community detection, where the goal is to automatically find groups of entities in social network data that are tightly connected. In particular, she devised methods and metrics that allow for more reliable interpretation of community detection results by social scientists. This highlights the interdisciplinary aspect of the work: it is not only about running algorithms and showing the results, but also in interpreting these results in a sensible way within the domain that the underlying data is representing.

“I learned much about the social sciences and the way social scientists do research. I also had the chance to dive into computer science / network science literature that was relevant for this project, so I also gained more expertise in my own domain.” — Dafne van Kuppervelt

The role of openness and sharing

One aspect that the Netherlands eScience Center has ample experience with, is data sharing and the FAIR data principles. Given that we work with large databases consisting of hundreds of millions of records of companies across the globe, a proper assessment of our data management against the FAIR principles and a systematic documentation of preprocessing steps have proven extemely helpful in professionalizing our research activities.

“A proper assessment of our data management against the FAIR principles and a systematic documentation of preprocessing steps have proven extemely helpful in professionalizing our research activities”

Long-term impact on the domain social science and society of the project

In general, the collaboration between social scientists and computer scientists is bound to last for a long time. With the ever-increasing amount of data that is nowadays available, social scientists will increasingly more often be confronted with challenges related to the size of the data and meaningful interpretation of patterns found in these big datasets. Similarly, computer scientists are confronted with more and more complex matters related to methods for the automated extraction of knowledge from large-scale data. With data-awareness of the average citizen increasing every year, society increasingly expects researchers, regardless of discipline, to make use of this data for answering today’s big research questions.

From left to right: Diliara Valeeva, Lucas van Straalen, Laurens Bogaardt, Javier Garcia-Bernardo, Eelke Heemskerk, Frank Takes and Milan Babic

Frank’s vision for his research area in three years

Social science research is becoming increasingly dependent on computational methods, and there is no reason to assume that this trend is not continued in the coming years. For example, the International Conference of Computational Social Science (IC2S2), which is the international flagship conference of computational social science is quickly growing in number of attendants, with over 400 researchers attending the 5th edition, held at University of Amsterdam in July 2019.

Photography: Michiel Wijnbergh | wijnbergh.nl