On October 2, 2019, sunny Santa Clara, California (US) will be the scene for the 3rd International Workshop on Mining Actionable Insights from Social Networks (MAISoN). We welcome original submissions on topics related to social network mining and related fields. […]
The Dutch Network Science Society is a society aimed at bringing together researchers in the Netherlands working on the topic of network science; the extraction of knowledge and insights from theoretical and empirical analysis of complex networks. On May 7 […]
As part of his MSc in Computer Science with Data Science specialization, Alain Fonhof analyzed real-world network data sets collected from online discussion forums on the dark net. It turns out that network centrality measures can succesfully identify and characterize […]
Network anomalies can for for example be spammers in communication networks, intruders in physical network systems or bots on social media. Master student Thomas Helling developed a new algorithm for finding such spammers, taking the awareness of nodes with respect […]
Network motifs are small building blocks consisting of a handful of nodes. Complex networks are made up out of countless of these little network patterns. Master student Hanjo Boekhout worked on algorithms for efficiently counting these motifs in a large-scale […]
About the CNS Lab
The Leiden Computational Network Science Lab (CNS Lab) researches algorithms and methods for knowledge discovery from real-world network data. Using both computational and machine learning methods, the goal is to unveil patterns in dynamic complex networks from a range of application domains. The CNS Lab is lead by Frank Takes and is part of the Department of Computer Science (LIACS) of Leiden University.