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Journal Article

Community structure unveils the path multiplicity in complex networks

Authors

Deng,  Ye
External Organizations;

Wu,  Jun
External Organizations;

Lu,  Xin
External Organizations;

Holme,  Petter
External Organizations;

Li,  Daqing
External Organizations;

Di,  Zengru
External Organizations;

Chen,  Guanrong
External Organizations;

/persons/resource/Juergen.Kurths

Kurths,  Jürgen
Potsdam Institute for Climate Impact Research;

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Deng_2026_s41467-026-70369-4.pdf
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Supplementary Material (public)

Deng_2026_41467_2026_70369_MOESM1_ESM_SI.pdf
(Supplementary material), 4MB

Citation

Deng, Y., Wu, J., Lu, X., Holme, P., Li, D., Di, Z., Chen, G., Kurths, J. (2026): Community structure unveils the path multiplicity in complex networks. - Nature Communications, 17, 2283.
https://doi.org/10.1038/s41467-026-70369-4


Cite as: https://publications.pik-potsdam.de/pubman/item/item_34757
Abstract
Networks with complex topologies describe numerous natural and social systems. Recent studies on path multiplicity have shown strong heterogeneity in shortest paths between node pairs in real-world networks. However, the mechanism underlying this phenomenon remains unexplored. Here, we reveal that community structure is a key factor shaping path multiplicity. To explore the intrinsic factors that influence path multiplicity, we first introduce the concept of relative path multiplicity and find that community structure is more strongly correlated with path multiplicity than other network metrics. Through targeted edge-rewiring experiments, we verify the link between path multiplicity and community structure. The underlying mechanism can be interpreted as an interface-driven effect that sharply increases the number of shortest paths. Inspired by these findings, we propose a tribal-structure-based network model that reproduces phenomena observed in real-world networks. Our work enhances the understanding of network organization, with potential applications in network design and optimization.