ArticleProceedings of the National Academy of Sciences of the United States of America2021
True scale-free networks hidden by finite size effects.
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 16 papers.
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Who cites it
16 citing papers in PubMed.
- Evolution and determinants of firm-level systemic risk in local production networks.PNAS nexus · 2026Article
- Jacobian Granger causality for count and binary data with applications to causal network inference.Scientific reports · 2025Article
- Scale-free Spatio-temporal Correlations in Conformational Fluctuations of Intrinsically Disordered Proteins.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality.Scientific reports · 2024Article
- Multi-scale analysis of the community structure of the Twitter discourse around the Italian general elections of September 2022.Scientific reports · 2024Article
- The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality.bioRxiv : the preprint server for biology · 2024Article
- The angiogenic growth of cities.Journal of the Royal Society, Interface · 2024Article
- The nature and nurture of network evolution.Nature communications · 2023Article
- Network medicine: an approach to complex kidney disease phenotypes.Nature reviews. Nephrology · 2023Review
- Circulation of a digital community currency.Scientific reports · 2023Article
- The emergence of scale-free fires in Australia.iScience · 2023Article
- Precision drug design againstFrontiers in cellular and infection microbiology · 2023Article
- Geometrical congruence, greedy navigability and myopic transfer in complex networks and brain connectomes.Nature communications · 2022Article
- Friend of a friend models of network growth.Royal Society open science · 2022Article
- Box scaling as a proxy of finite size correlations.Scientific reports · 2021Article
- Scale free is not rare in international trade networks.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statistical testing of the validity of power law distributions of network degrees. Specifically, we analyze by finite size scaling analysis the datasets of real networks to check whether the purported departures from power law behavior are due to the finiteness of sample size. We find that a large number of the networks follows a finite size scaling hypothesis without any self-tuning. This is the case of biological protein interaction networks, technological computer and hyperlink networks, and informational networks in general. Marked deviations appear in other cases, especially involving infrastructure and transportation but also in social networks. We conclude that underlying scale invariance properties of many naturally occurring networks are extant features often clouded by finite size effects due to the nature of the sample data.
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