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Novel centrality measures and applications to underground networks

Author

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  • Mussone, L.
  • Viseh, H.
  • Notari, R.

Abstract

Two novel centrality indices, PathRank and Icentr, are defined. PathRank is a generalization of the PageRank algorithm, suitable to rank nodes of undirected graphs according to number and weight of paths in the graph. Icentr ranks the nodes of the graph by means of a combination of the weights of nodes and edges, scaled according to the distance from each node, one at a time. We apply the two novel indices to underground transportation networks, since these networks represent an infrastructural backbone for the transportation system of most big cities over the world. The characterization of the most important components of those networks and the simulation of their responses when they stop working properly, are vital for maintaining the mobility service at a desirable level. Since there are different ways to associate a graph to an underground network according to the degree of detail and aims of the study, we describe the methodology we adopted to associate a graph to such a network. The methodology was applied to 34 underground networks of worldwide cities, and the resulting graphs constitute the reference dataset. A detailed study of both Boston network and the dataset is proposed as prototypal for either a graph alone or all graphs in a dataset. Results show how different features of graphs are revealed by the two novel indices.

Suggested Citation

  • Mussone, L. & Viseh, H. & Notari, R., 2022. "Novel centrality measures and applications to underground networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
  • Handle: RePEc:eee:phsmap:v:589:y:2022:i:c:s0378437121008633
    DOI: 10.1016/j.physa.2021.126595
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    References listed on IDEAS

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    1. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    2. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
    3. Wu, Xingtang & Dong, Hairong & Tse, Chi Kong & Ho, Ivan W.H. & Lau, Francis C.M., 2018. "Analysis of metro network performance from a complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 553-563.
    4. Wang, Fahui & Antipova, Anzhelika & Porta, Sergio, 2011. "Street centrality and land use intensity in Baton Rouge, Louisiana," Journal of Transport Geography, Elsevier, vol. 19(2), pages 285-293.
    5. Dimitrios Tsiotas & Serafeim Polyzos, 2015. "Introducing a new centrality measure from the transportation network analysis in Greece," Annals of Operations Research, Springer, vol. 227(1), pages 93-117, April.
    6. Dimitrov, Stavri Dimitri & Ceder, Avishai (Avi), 2016. "A method of examining the structure and topological properties of public-transport networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 373-387.
    7. Wang, Yuhong & Cullinane, Kevin, 2016. "Determinants of port centrality in maritime container transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 326-340.
    8. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    9. Wang, Jiaoe & Mo, Huihui & Wang, Fahui & Jin, Fengjun, 2011. "Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach," Journal of Transport Geography, Elsevier, vol. 19(4), pages 712-721.
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    Cited by:

    1. Col, Alcebiades Dal & Petronetto, Fabiano, 2023. "Graph regularization centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).

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