Maximum Entropy Hub

During the years, the NETWORKS unit contributed strongly to the development of maximum-entropy methods for the analysis of complex networks [1]. In the dedicated webpage Maximum Entropy Hub, we collect all the codes produced by our group in order to implement the various models.

[1] Cimini, G., Squartini, T., Saracco, F. et al. The statistical physics of real-world networks. Nat Rev Phys 1, 58–71 (2019).

Detecting Core-Perifery by Surprise

At the following link, you can find the code for a method to detect statistically significant bimodular structures, i.e. either bipartite or core-periphery ones. It is based on a modification of the so-called "surprise" metric proposed for detecting communities in networks. The present variant allows for bimodular node partitions to be revealed, by letting links to be placed either 1) within the core part and between the core and the periphery parts or 2) just between the (empty) layers of a bipartite network. More details can be found in the original article [1].

[1] J. van Lidth de Jeude, G. Caldarelli and T. Squartini, EPL (Europhysics Letters), Volume 125, Number 6 (2019)