Network motifs uncovering hidden characteristics of urban public transportation

Iovanovici, Alexandru; Pellegrini, Lilla; Moscovici, Anca-Maria; Leba, Monica

doi:10.1109/informatics47936.2019.9119289

Cited by 5 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of other studies have examined motifs in transportation networks (such as road networks and airline networks). [21] used motifs on transportation networks to better understand their topology. [22], in calculating motifs for airline networks found that adjusting the number of proper network motifs is useful to optimize the overall structure of airline networks for profitable air transport.…”

Section: Introductionmentioning

confidence: 99%

Latent Sub-structural Resilience Mechanisms in Temporal Human Mobility Networks during Urban Flooding

Rajput¹,

Mostafavi²

2022

Preprint

View full text Add to dashboard Cite

In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilized high-resolution aggregated location-based data to construct temporal human mobility networks in Harris County, Texas (Houston metropolitan area) in the context of the 2017 Hurricane Harvey. Using the constructed temporal network models, we examined characteristics such as motif distribution, motif persistence and temporal stability, and motif attributes to reveal latent substructural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persists in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration is heterogeneous across different network types. Also, perturbation impacts persist at the sub-structure level while global topological network properties might indicate the network has recovered. The patterns of impact and recovery at the global-network scale is influenced by more abundant motifs; however, less abundant motifs (which are shown to have more stability during steady state) experience greater sustained impacts and take longer to recover. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks), it is essential to examine the microstructures and their perturbation impacts and recovery. The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and to monitor recovery in affected communities based on the patterns of impact and recovery in human mobility networks at both sub-structure and global-network levels.

show abstract

Section: Introductionmentioning

confidence: 99%

Latent Sub-structural Resilience Mechanisms in Temporal Human Mobility Networks during Urban Flooding

Rajput¹,

Mostafavi²

2022

Preprint

View full text Add to dashboard Cite

show abstract

Latent sub-structural resilience mechanisms in temporal human mobility networks during urban flooding

Rajput

Mostafavi

2023

Sci Rep

View full text Add to dashboard Cite

In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilize high-resolution aggregated location-based data to construct temporal human mobility networks in Houston in the context of the 2017 Hurricane Harvey. We examine motif distribution, motif persistence, temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persist in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration are heterogeneous across different network types. Also, while perturbation impacts persist at the sub-structure level, global topological network properties indicate that the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks). The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and monitor recovery in affected communities.

show abstract

A Neuroevolution-Inspired Scheme for Generating Robust Internet of Things

Zhang

Chen

et al. 2022

2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

View full text Add to dashboard Cite

Network motifs uncovering hidden characteristics of urban public transportation

Cited by 5 publications

References 12 publications

Latent Sub-structural Resilience Mechanisms in Temporal Human Mobility Networks during Urban Flooding

Latent Sub-structural Resilience Mechanisms in Temporal Human Mobility Networks during Urban Flooding

Latent sub-structural resilience mechanisms in temporal human mobility networks during urban flooding

A Neuroevolution-Inspired Scheme for Generating Robust Internet of Things

Contact Info

Product

Resources

About