  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.
