Discovering the Hidden Community Structure of Public Transportation Networks

László Hajdu (), András Bóta (), Miklós Krész (), Alireza Khani () and Lauren M. Gardner ()
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László Hajdu: University of Szeged
András Bóta: Umeå University
Miklós Krész: University of Szeged
Alireza Khani: University of Minnesota Twin Cities
Lauren M. Gardner: University of New South Wales

Networks and Spatial Economics, 2020, vol. 20, issue 1, No 8, 209-231

Abstract: Abstract Advances in public transit modeling and smart card technologies can reveal detailed contact patterns of passengers. A natural way to represent such contact patterns is in the form of networks. In this paper we utilize known contact patterns from a public transit assignment model in a major metropolitan city, and propose the development of two novel network structures, each of which elucidate certain aspects of passenger travel behavior. We first propose the development of a transfer network, which can reveal passenger groups that travel together on a given day. Second, we propose the development of a community network, which is derived from the transfer network, and captures the similarity of travel patterns among passengers. We then explore the application of each of these network structures to identify the most frequently used travel paths, i.e., routes and transfers, in the public transit system, and model epidemic spreading risk among passengers of a public transit network, respectively. In the latter our conclusions reinforce previous observations, that routes crossing or connecting to the city center in the morning and afternoon peak hours are the most “dangerous” during an outbreak.

Keywords: Network modeling; Public transportation; Community structure; Infrastructure security (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11067-019-09476-3

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