ArticleNature communications2023
Hyper-cores promote localization and efficient seeding in higher-order processes.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Contrasting Resilience Diagnostics in Route-Preserving Multimodal Transit Hypergraphs.Entropy (Basel, Switzerland) · 2026Article
- Rumor propagation on hypergraphs.Nature communications · 2026Article
- The microscale organization of directed hypergraphs.Communications physics · 2026Article
- Higher-order interactions shape collective human behaviour.Nature human behaviour · 2025Review
- A small set of critical hyper-motifs governs heterogeneous flow-weighted network resilience.Nature communications · 2025Article
- Identifying Influential Nodes Based on Evidence Theory in Complex Network.Entropy (Basel, Switzerland) · 2025Article
- The temporal dynamics of group interactions in higher-order social networks.Nature communications · 2024Article
- Legal hypergraphs.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2024Article
- Hyper-cores promote localization and efficient seeding in higher-order processes.Nature communications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Going beyond networks, to include higher-order interactions of arbitrary sizes, is a major step to better describe complex systems. In the resulting hypergraph representation, tools to identify structures and central nodes are scarce. We consider the decomposition of a hypergraph in hyper-cores, subsets of nodes connected by at least a certain number of hyperedges of at least a certain size. We show that this provides a fingerprint for data described by hypergraphs and suggests a novel notion of centrality, the hypercoreness. We assess the role of hyper-cores and nodes with large hypercoreness in higher-order dynamical processes: such nodes have large spreading power and spreading processes are localized in central hyper-cores. Additionally, in the emergence of social conventions very few committed individuals with high hypercoreness can rapidly overturn a majority convention. Our work opens multiple research avenues, from comparing empirical data to model validation and study of temporally varying hypergraphs.
Identifiers
What OpenQuestion holds
Registered trials
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.