Characterizing Regional Importance in Cities with Human Mobility Motifs in Metro Networks

TL;DR

This paper introduces a novel motif-based framework for constructing human mobility networks from metro data, significantly improving regional importance characterization over traditional methods by leveraging higher-order mobility motifs.

Contribution

It proposes two new network construction frameworks based on mobility motifs and demonstrates their superiority in urban regional importance analysis using large-scale metro data.

Findings

Motif-based networks outperform classic mobility networks.

The motif-wise framework significantly improves regional importance characterization.

Enhanced dependency modeling within mobility motifs enhances network analysis.

Abstract

Uncovering higher-order spatiotemporal dependencies within human mobility networks offers valuable insights into the analysis of urban structures. In most existing studies, human mobility networks are typically constructed by aggregating all trips without distinguishing who takes which specific trip. Instead, we claim individual mobility motifs, higher-order structures generated by daily trips of people, as fundamental units of human mobility networks. In this paper, we propose two network construction frameworks at the level of mobility motifs in characterizing regional importance in cities. Firstly, we enhance the structural dependencies within mobility motifs and proceed to construct mobility networks based on the enhanced mobility motifs. Secondly, taking inspiration from PageRank, we speculate that people would allocate values of importance to destinations according to their trip intentions. A motif-wise network construction framework is proposed based on the established mechanism. Leveraging large-scale metro data across cities, we construct three types of human mobility networks and characterize the regional importance by node importance indicators. Our comparison results suggest that the motif-based mobility network outperforms the classic mobility network, thus highlighting the efficacy of the introduced human mobility motifs. Finally, we demonstrate that the performance in characterizing the regional importance is significantly improved by our motif-wise framework.