A benchmark model to assess community structure in evolving networks

Detecting the time evolution of the community structure of networks is crucial to identify major changes in the internal organization of many complex systems, which may undergo important endogenous or exogenous events. This analysis can be done in two ways: considering each snapshot as an independent community detection problem or taking into account the whole evolution of the network. In the first case, one can apply static methods on the temporal snapshots, which correspond to configurations of the system in short time windows, and match afterward the communities across layers. Alternatively, one can develop dedicated dynamic procedures so that multiple snapshots are simultaneously taken into account while detecting communities, which allows us to keep memory of the flow. To check how well a method of any kind could capture the evolution of communities, suitable benchmarks are needed. Here we propose a model for generating simple dynamic benchmark graphs, based on stochastic block models. In them, the time evolution consists of a periodic oscillation of the system's structure between configurations with built-in community structure. We also propose the extension of quality comparison indices to the dynamic scenario.

[1]  H. J. Mclaughlin,et al.  Learn , 2002 .

[2]  W. Marsden I and J , 2012 .

[3]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[4]  E. B. Wilson PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES. , 1919, Science.

[5]  J. Rogers Chaos , 1876 .

[6]  R. Rosenfeld Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[7]  Daniel P. Miranker,et al.  Proceedings of the 2008 - IEEE 24th International Conference on Data Engineering Workshop, ICDE'08 , 2008, ICDE 2008.

[8]  David K Campbell,et al.  Editorial: The pre-history of Chaos-An Interdisciplinary Journal of Nonlinear Science. , 2015, Chaos.

[9]  D. Steinley Journal of Classification , 2004, Vegetatio.

[10]  P. Steerenberg,et al.  Targeting pathophysiological rhythms: prednisone chronotherapy shows sustained efficacy in rheumatoid arthritis. , 2010, Annals of the rheumatic diseases.