Leiden CNS @ EUSN 2021

Our group is presenting two papers at the 5th European Conference on Social Networks, EUSN 2021: Tue Sep 7, Session S1: 10:00-10:20 – Process-driven network analysis of passing in professional football, by Carolina Mattsson and Frank Takes Thu Sep 9, Session S9: 10:20-10:40 – Population-scale social network analysis, by Frank…

Leiden CNS @ IC2S2 2021

Our Leiden Computational Network Science group is present at the 7th International Conference on Computational Social Science (IC2S2 2021) with a number of presentations: Teodoro Criscione and Carolina Mattsson (poster presentation): Network Analysis of Sarafu Currency System (abstract) Rachel de Jong, Mark van der Loo and Frank Takes (poster presentation): Measuring Anonymity in Complex  Networks (abstract) Frank…

Leiden CNS @ Networks 2021

Various memebers of the Leiden CNS group are present at the Networks 2021 conference, which is the Joint Sunbelt and NetSci Conference. It is the first combined meeting of the International Network for Social Network Analysis (Sunbelt XLI), and the Network Science Society (NetSci 2021); two communities that the Leiden…

Hanjo Boekhout starts as PhD candidate

Hanjo Boekhout MSc started as a PhD candidate in the Computational Network Science group in August of 2020. Both his Bachelor’s and Master’s degree in Computer Science, with a specialization in “Computer Science and Advanced Data Analytics”, were obtained with honor (cum laude) at Leiden University. During his Master’s studies,…

Carolina Mattsson starts as postdoc

dr. Carolina Mattsson started as a postdoctoral researcher in the Computational Network Science group in May of 2020. She holds a doctorate in Network Science from Northeastern University, where she was an NSF Graduate Research Fellow. Her undergraduate degrees (Physics & International Relations) are from Lehigh University. In her research,…

Andre Beijen starts as PhD candidate

Andre Beijen started his PhD project in the fall of 2019 in the Computational Network Science group at LIACS, Leiden University. Andre has a degree in applied physics from Technical University Delft, where he graduated in statistical signal processing. Since then he worked worked in high tech environments, such as…

Efficiently counting complex multilayer temporal motifs in large-scale networks

In a new paper titled “Efficiently counting complex multilayer temporal motifs in large-scale networks” we detail our approach to counting multilayer temporal motifs in networks with partial timing. The code (see Bitbucket) builds upon the well-known Stanford Network Analysis (SNAP) package. H.D. Boekhout, W.A. Kosters and F.W. Takes, Efficiently Counting Complex Multilayer Temporal…