Spatial Networks

@article{Barthelemy2010SpatialN,
  title={Spatial Networks},
  author={Marc Barthelemy},
  journal={ArXiv},
  year={2010},
  volume={abs/1010.0302}
}
  • M. Barthelemy
  • Published 2 October 2010
  • Computer Science, Physics, Biology
  • ArXiv
Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields ranging from urbanism to… Expand
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References

SHOWING 1-10 OF 370 REFERENCES
Connectivity distribution of spatial networks.
TLDR
It is shown that for regular spatial densities, the corresponding spatial network has a connectivity distribution decreasing faster than an exponential, and that scale-free networks with a power law decreasing connectivity distribution are obtained when a certain information measure of the node distribution diverges. Expand
The architecture of complex weighted networks.
TLDR
This work studies the scientific collaboration network and the world-wide air-transportation network, which are representative examples of social and large infrastructure systems, respectively, and defines appropriate metrics combining weighted and topological observables that enable it to characterize the complex statistical properties and heterogeneity of the actual strength of edges and vertices. Expand
Structural properties of spatially embedded networks
We study the effects of spatial constraints on the structural properties of networks embedded in one- or two-dimensional space. When nodes are embedded in space, they have a well-defined EuclideanExpand
Evolution of networks
TLDR
The recent rapid progress in the statistical physics of evolving networks is reviewed, and how growing networks self-organize into scale-free structures is discussed, and the role of the mechanism of preferential linking is investigated. Expand
Vulnerability of weighted networks
In real networks complex topological features are often associated with a diversity of interactions as measured by the weights of the links. Moreover, spatial constraints may also play an importantExpand
The effects of spatial constraints on the evolution of weighted complex networks
Motivated by the empirical analysis of the air transportation system, we define a network model that includes geographical attributes along with topological and weight (traffic) properties. TheExpand
Public transport networks: empirical analysis and modeling
TLDR
A simple model reproduces many of the identified PTN properties by growing networks of attractive self-avoiding walks, including a surprising geometrical behavior with respect to the two-dimensional geographical embedding and an unexpected attraction between transport routes. Expand
Measuring the Structure of Road Networks
TLDR
The results show that the differentiated structures of road networks can be evaluated by the measure of entropy; predefined connection patterns of arterial roads can be identified and quantified by the measures of ringness, webness, beltness, circuitness, and treeness. Expand
Centrality in networks of urban streets.
TLDR
A comprehensive study of centrality distributions over geographic networks of urban streets indicates that a spatial analysis, that is grounded not on a single centrality assessment but on a set of different centrality indices, allows an extended comprehension of the city structure. Expand
Assessing the relevance of node features for network structure
TLDR
This paper proposes a general indicator Θ, based on entropy measures, to quantify the dependence of a network's structure on a given set of features, and applies this method to social networks of friendships in U.S. schools, to the protein-interaction network of Saccharomyces cerevisiae and to the U.s. airport network, showing that the proposed measure provides information that complements other known measures. Expand
...
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4
5
...