Small worlds and clustering in spatial networks
Marián Boguñá, Dmitri Krioukov, Pedro Almagro, M. Ángeles Serrano
Abstract
The authors derive the necessary and sufficient conditions for a spatial network model to be a small world and to have nonzero clustering at the same time. Both homogeneous and heterogeneous spatial network models are considered. The paper shows that under additional maximum-entropy requirements to the heterogeneous models, the unique solution is random hyperbolic graphs.
Topics & Concepts
Cluster analysisHomogeneousComputer scienceSpatial analysisData miningSpatial networkMathematicsTheoretical computer scienceSmall-world networkHeterogeneous networkArtificial intelligenceRandom graphClustering coefficientNetwork topologyNetwork modelComplex networkData modelingSpatial ecologyComplex Network Analysis TechniquesStatistical Mechanics and EntropyHuman Mobility and Location-Based Analysis