ArticleScience advances2018
A physical model for efficient ranking in networks.
Article in Science advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Hierarchy and ranking in fencing and tennis.Scientific reports · 2026Article
- Next-generation antiviral peptides: AI-driven design, translational delivery platforms, and future therapeutic directions.Virus research · 2025Review
- Luck, skill, and depth of competition in games and social hierarchies.Science advances · 2024Article
- Gender and retention patterns among U.S. faculty.Science advances · 2023Article
- Influence and influenceability: global directionality in directed complex networks.Royal Society open science · 2023Article
- Strong connectivity in real directed networks.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Labor advantages drive the greater productivity of faculty at elite universities.Science advances · 2022Article
- Article
- The interplay between ranking and communities in networks.Scientific reports · 2022Article
- RETRACTED: An Adaptive Hierarchical Network Model for Studying the Structure of Economic NetworkEntropy (Basel, Switzerland) · 2022Article
- Social hierarchies and social networks in humans.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- A guide to choosing and implementing reference models for social network analysis.Biological reviews of the Cambridge Philosophical Society · 2021Review
- Emergence of hierarchy in networked endorsement dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- How directed is a directed network?Royal Society open science · 2020Article
- Structure and dynamical behavior of non-normal networks.Science advances · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a physically inspired model and an efficient algorithm to infer hierarchical rankings of nodes in directed networks. It assigns real-valued ranks to nodes rather than simply ordinal ranks, and it formalizes the assumption that interactions are more likely to occur between individuals with similar ranks. It provides a natural statistical significance test for the inferred hierarchy, and it can be used to perform inference tasks such as predicting the existence or direction of edges. The ranking is obtained by solving a linear system of equations, which is sparse if the network is; thus, the resulting algorithm is extremely efficient and scalable. We illustrate these findings by analyzing real and synthetic data, including data sets from animal behavior, faculty hiring, social support networks, and sports tournaments. We show that our method often outperforms a variety of others, in both speed and accuracy, in recovering the underlying ranks and predicting edge directions.
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.