Evidence map›Paper›PMID 41792145›Full record

ArticleNature communications2026

Community structure unveils the path multiplicity in complex networks.

Ye Deng, Jun Wu, Xin Lu, Petter Holme, Daqing Li, Zengru Di, Guanrong Chen, Jürgen Kurths

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ye DengDepartment of Systems Science, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai, China.
Jun WuDepartment of Systems Science, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai, China. junwu@bnu.edu.cn.ORCID http://orcid.org/0000-0002-1154-6071
Xin LuCollege of Systems Engineering, National University of Defense Technology, Changsha, China. xin.lu.lab@outlook.com.ORCID http://orcid.org/0000-0002-3547-6493
Petter HolmeDepartment of Computer Science, Aalto University, Espoo, Finland.ORCID http://orcid.org/0000-0003-2156-1096
Daqing LiSchool of Reliability and Systems Engineering, Beihang University, Beijing, China. daqingl@buaa.edu.cn.ORCID http://orcid.org/0000-0001-9166-351X
Zengru DiDepartment of Systems Science, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai, China.ORCID http://orcid.org/0000-0002-5240-298X
Guanrong ChenDepartment of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China.ORCID http://orcid.org/0000-0003-1381-7418
Jürgen KurthsResearch Domain Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.ORCID http://orcid.org/0000-0002-5926-4276

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72025405National Natural Science Foundation of China (National Science Foundation of China) 72201035National Natural Science Foundation of China (National Science Foundation of China) 72225012National Natural Science Foundation of China (National Science Foundation of China) 72288101National Natural Science Foundation of China (National Science Foundation of China) 72421002National Natural Science Foundation of China (National Science Foundation of China) 72571031National Natural Science Foundation of China (National Science Foundation of China) 92467302Natural Science Foundation of Guangdong Province (Guangdong Natural Science Foundation) 2025A1515011586
6 · The paper itself

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.

Identifiers

PMID41792145
PMCPMC12972315

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.