ArticleNature communications2019
A Pólya urn approach to information filtering in complex networks.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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Who cites it
16 citing papers in PubMed.
- Quantifying edge relevance for epidemic spreading via the semi-metric topology of complex networks.Journal of physics. Complexity · 2025Article
- An egonet based approach to effective weighted network comparison.Scientific reports · 2025Article
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- Exploring weighted network backbone extraction: A comparative analysis of structural techniques.PloS one · 2025Article
- Article
- An evaluation tool for backbone extraction techniques in weighted complex networks.Scientific reports · 2023Article
- Estimation of reinforced urn processes under left-truncation and right-censoring.Royal Society open science · 2023Article
- Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs.PLoS computational biology · 2023Article
- Simplicial Persistence of Financial Markets: Filtering, Generative Processes and Structural Risk.Entropy (Basel, Switzerland) · 2022Article
- Analysis of the Structure and Dynamics of European Flight Networks.Entropy (Basel, Switzerland) · 2022Article
- Article
- backbone: An R package to extract network backbones.PloS one · 2022Article
- Phenotype correlations reveal the relationships of physiological systems underlying human ageing.Aging cell · 2021Article
- Configuration models as an urn problem.Scientific reports · 2021Article
- Peer-to-peer loan acceptance and default prediction with artificial intelligence.Royal Society open science · 2020Article
- The structured backbone of temporal social ties.Nature communications · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing availability of data demands for techniques to filter information in large complex networks of interactions. A number of approaches have been proposed to extract network backbones by assessing the statistical significance of links against null hypotheses of random interaction. Yet, it is well known that the growth of most real-world networks is non-random, as past interactions between nodes typically increase the likelihood of further interaction. Here, we propose a filtering methodology inspired by the Pólya urn, a combinatorial model driven by a self-reinforcement mechanism, which relies on a family of null hypotheses that can be calibrated to assess which links are statistically significant with respect to a given network's own heterogeneity. We provide a full characterization of the filter, and show that it selects links based on a non-trivial interplay between their local importance and the importance of the nodes they belong to.
Identifiers
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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.