Abstract
Studies on small-world networks have received intensive interdisciplinary attention during the past several years. It is well-known among researchers that a small-world network is often characterized by high connectivity and clustering, but so far there exist few effective approaches to evaluate small-world properties, especially for spatial networks. This paper proposes a method to examine the small-world properties of spatial networks from the perspective of network autocorrelation. Two network autocorrelation statistics, Moran’s I and Getis–Ord’s G, are used to monitor the structural properties of networks in a process of “rewiring” networks from a regular to a random network. We discovered that Moran’s I and Getis–Ord’s G tend to converge and have relatively low values when properties of small-world networks emerge. Three transportation networks at the national, metropolitan, and intra-city levels are analyzed using this approach. It is found that spatial networks at these three scales possess small-world properties when the correlation lag distances reach certain thresholds, implying that the manifestation of small-world phenomena result from the interplay between the network structure and the dynamics taking place on the network.
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Acknowledgments
Partial support by the Southwest University Transportation Research Center for this project is gratefully acknowledged. Three anonymous reviewers provided valuable comments that substantially improved our arguments. We would also like to thank Jose Gavinha and Gabe Rolland for their comments on an earlier draft of this paper. We are fully responsible for any remaining errors.
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Xu, Z., Sui, D.Z. Small-world characteristics on transportation networks: a perspective from network autocorrelation. J Geograph Syst 9, 189–205 (2007). https://doi.org/10.1007/s10109-007-0045-1
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DOI: https://doi.org/10.1007/s10109-007-0045-1