ArticleProceedings of the National Academy of Sciences of the United States of America2021
Scaling up real networks by geometric branching growth.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Reconstructing the evolution history of networked complex systems.Nature communications · 2024Article
- The D-Mercator method for the multidimensional hyperbolic embedding of real networks.Nature communications · 2023Article
- Evolutionary dynamics on sequential temporal networks.PLoS computational biology · 2023Article
- Article
- Detecting the ultra low dimensionality of real networks.Nature communications · 2022Article
- Scaling up real networks by geometric branching growth.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real networks often grow through the sequential addition of new nodes that connect to older ones in the graph. However, many real systems evolve through the branching of fundamental units, whether those be scientific fields, countries, or species. Here, we provide empirical evidence for self-similar growth of network structure in the evolution of real systems-the journal-citation network and the world trade web-and present the geometric branching growth model, which predicts this evolution and explains the symmetries observed. The model produces multiscale unfolding of a network in a sequence of scaled-up replicas preserving network features, including clustering and community structure, at all scales. Practical applications in real instances include the tuning of network size for best response to external influence and finite-size scaling to assess critical behavior under random link failures.
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Registered trials
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