Data-Driven Analysis of Real-World Networks and their Model-Generated Counterparts – running

Data-driven analysis of complex networks has been in the focus of research for decades. An important research question is to study how well real networks can be described with a small selection of metrics, furthermore how well network models can capture the relations between graph metrics observed in real networks.
First, we have to calculate several graph metrics of 500 real-world networks, then based on a selection of the metrics we calibrate 4 well-known network models, which are computationally expensive problems.

Project owner:
Nagy Marcell (Matematika Intézet)
Matematika Intézet (TTK-MATH)