Discovering the Hidden Community Structure of Public Transportation Networks
Advances in public transit modeling and smart card technologies can reveal detailedcontact patterns of passengers. A natural way to represent such contact patterns is inthe form of networks. In this paper we utilize known contact patterns from a publictransit assignment model in a major metropolitan...
Elmentve itt :
| Szerzők: | |
|---|---|
| Dokumentumtípus: | Cikk |
| Megjelent: |
2020
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| Sorozat: | NETWORKS AND SPATIAL ECONOMICS: A JOURNAL OF INFRASTRUCTURE MODELING AND COMPUTATION
20 No. 1 |
| Tárgyszavak: | |
| doi: | 10.1007/s11067-019-09476-3 |
| mtmt: | 30925919 |
| Online Access: | http://publicatio.bibl.u-szeged.hu/26076 |
| LEADER | 02158nab a2200265 i 4500 | ||
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| 005 | 20230110142309.0 | ||
| 008 | 230110s2020 hu o 0|| Angol d | ||
| 022 | |a 1566-113X | ||
| 024 | 7 | |a 10.1007/s11067-019-09476-3 |2 doi | |
| 024 | 7 | |a 30925919 |2 mtmt | |
| 040 | |a SZTE Publicatio Repozitórium |b hun | ||
| 041 | |a Angol | ||
| 100 | 1 | |a Hajdu László | |
| 245 | 1 | 0 | |a Discovering the Hidden Community Structure of Public Transportation Networks |h [elektronikus dokumentum] / |c Hajdu László |
| 260 | |c 2020 | ||
| 300 | |a 209-231 | ||
| 490 | 0 | |a NETWORKS AND SPATIAL ECONOMICS: A JOURNAL OF INFRASTRUCTURE MODELING AND COMPUTATION |v 20 No. 1 | |
| 520 | 3 | |a Advances in public transit modeling and smart card technologies can reveal detailedcontact patterns of passengers. A natural way to represent such contact patterns is inthe form of networks. In this paper we utilize known contact patterns from a publictransit assignment model in a major metropolitan city, and propose the developmentof two novel network structures, each of which elucidate certain aspects of passengertravel behavior. We first propose the development of a transfer network, which canreveal passenger groups that travel together on a given day. Second, we propose thedevelopment of a community network, which is derived from the transfer network,and captures the similarity of travel patterns among passengers. We then explorethe application of each of these network structures to identify the most frequentlyused travel paths, i.e., routes and transfers, in the public transit system, and modelepidemic spreading risk among passengers of a public transit network, respectively.In the latter our conclusions reinforce previous observations, that routes crossing orconnecting to the city center in the morning and afternoon peak hours are the most“dangerous” during an outbreak. | |
| 650 | 4 | |a Számítás- és információtudomány | |
| 700 | 0 | 1 | |a Bóta András |e aut |
| 700 | 0 | 1 | |a Krész Miklós |e aut |
| 700 | 0 | 1 | |a Khani Alireza |e aut |
| 700 | 0 | 1 | |a Gardner Lauren M. |e aut |
| 856 | 4 | 0 | |u http://publicatio.bibl.u-szeged.hu/26076/1/NETS_paper.pdf |z Dokumentum-elérés |