Dresden 2014 – scientific programme

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SOE: Fachverband Physik sozio-ökonomischer Systeme

SOE 16: Networks - Statistics and Dynamics (joint with BP and DY)

SOE 16.6: Talk

Wednesday, April 2, 2014, 16:15–16:30, ZEU 118

Hierarchical block structures and high-resolution model selection in large networks — •Tiago P. Peixoto — Universität Bremen, Germany

Many social, technological, and biological networks are composed of modules, which represent groups of nodes which have a similar role in the functioning of the network. The problem of detecting and characterizing these modules is a central one in the broad field of complex systems. However most existing methods used to obtain the modular structure of networks suffer from serious problems, such as the resolution limit on the size of communities. This phenomenon occurs for the very popular approach of modularity optimization, but also for more principled ones based on statistical inference and model selection. Here I construct a nested generative model which, through a complete description of the entire network hierarchy at multiple scales, is capable of avoiding this limitation, and enables the detection of modular structure at levels far beyond those possible by current approaches. Even with this increased resolution, the method is based on the principle of parsimony, and is capable of separating signal from noise. Furthermore, it fully generalizes other approaches in that it is not restricted to purely assortative mixing patterns, directed or undirected graphs, and ad hoc hierarchical structures such as binary trees..

References: [1] Tiago P. Peixoto, Phys. Rev. Lett. 110 14 148701 (2013); [2] Tiago P. Peixoto, arXiv: 1310.4377; [3] Tiago P. Peixoto, arXiv: 1310.4378