2007/01/02 by Stefan Thurner, Fragiskos Kyriakopoulos, Constantino Tsallis · 41 citations
Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Artificial intelligence #Cluster analysis #Clustering coefficient #Combinatorics #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Complex network #Computer science #Data mining #Degree (music) #Degree distribution #Discrete mathematics #Exponential function #Exponential growth #Exponential random graph models #Graph #Limit (mathematics) #Mathematics #Metric (unit) #Metric space #Network dynamics #Network model #Network topology #Parameter space #Physics #Preferential attachment #Random graph #Space (punctuation) #Statistical Mechanics and Entropy #Statistical physics #Statistics #Theoretical computer science #cond-mat.stat-mech
paper · pdf · doi:10.1103/physreve.76.036111
published in Physical Review E 76(3), 036111 (American Physical Society) · 11 pages 8 figs
arxiv created 2007/01/02 · openalex publication_date 2007/09/17 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We introduce a dynamical network model which unifies a number of network families which are individually known to exhibit q-exponential degree distributions. The present model dynamics incorporates static (nongrowing) self-organizing networks, preferentially growing networks, and (preferentially) rewiring networks. Further, it exhibits a natural random graph limit. The proposed model generalizes network dynamics to rewiring and growth modes which depend on internal topology as well as on a metric imposed by the space they are embedded in. In all of the networks emerging from the presented model we find q-exponential degree distributions over a large parameter space. We comment on the parameter dependence of the corresponding entropic index q for the degree distributions, and on the behavior of the clustering coefficients and neighboring connectivity distributions.