Evidence map›Paper›PMID 33850012›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Emergence of hierarchy in networked endorsement dynamics.

Mari Kawakatsu, Philip S Chodrow, Nicole Eikmeier, Daniel B Larremore

Open access · greenAbstract read
In one paragraph

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 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.5field-weighted citation impact, top 14% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. The interdependence of relational and material wealth inequality in Pemba, Zanzibar.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  4. Article
  5. Dynamics of ranking.Nature communications · 2022
    Article
  6. Social hierarchies and social networks in humans.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  7. Quantifying the dynamics of nearly 100 years of dominance hierarchy research.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  8. The dynamics of dominance: open questions, challenges and solutions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  9. Costs dictate strategic investment in dominance interactions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  10. A roadmap towards predicting species interaction networks (across space and time).Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Review
  11. From equality to hierarchy.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  12. Emergence of hierarchy in networked endorsement dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 1 country.

Mari KawakatsuProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ 08544; mari.kawakatsu@princeton.edu phil@math.ucla.edu eikmeier@grinnell.edu daniel.larremore@colorado.edu.ORCID 0000-0003-2072-6653
Philip S ChodrowOperations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139; mari.kawakatsu@princeton.edu phil@math.ucla.edu eikmeier@grinnell.edu daniel.larremore@colorado.edu.ORCID 0000-0001-5667-490X
Nicole EikmeierDepartment of Computer Science, Grinnell College, Grinnell, IA 50112; mari.kawakatsu@princeton.edu phil@math.ucla.edu eikmeier@grinnell.edu daniel.larremore@colorado.edu.ORCID 0000-0002-4789-2275
Daniel B LarremoreDepartment of Computer Science, University of Colorado Boulder, Boulder, CO 80309; mari.kawakatsu@princeton.edu phil@math.ucla.edu eikmeier@grinnell.edu daniel.larremore@colorado.edu.ORCID 0000-0001-5273-5234
Grinnell College · USPrinceton University · USUniversity of California, Los Angeles · USUniversity of Colorado Boulder · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many social and biological systems are characterized by enduring hierarchies, including those organized around prestige in academia, dominance in animal groups, and desirability in online dating. Despite their ubiquity, the general mechanisms that explain the creation and endurance of such hierarchies are not well understood. We introduce a generative model for the dynamics of hierarchies using time-varying networks, in which new links are formed based on the preferences of nodes in the current network and old links are forgotten over time. The model produces a range of hierarchical structures, ranging from egalitarianism to bistable hierarchies, and we derive critical points that separate these regimes in the limit of long system memory. Importantly, our model supports statistical inference, allowing for a principled comparison of generative mechanisms using data. We apply the model to study hierarchical structures in empirical data on hiring patterns among mathematicians, dominance relations among parakeets, and friendships among members of a fraternity, observing several persistent patterns as well as interpretable differences in the generative mechanisms favored by each. Our work contributes to the growing literature on statistically grounded models of time-varying networks.

Indexed as

Hierarchy, SocialSocial BehaviorAnimalsBehavior, AnimalHumansModels, TheoreticalSocial DominanceSocial Networkingcritical transitionsdominance hierarchiesdynamical systemsnetwork sciencestatistical inference

Identifiers

PMID33850012
PMCPMC8072324
OpenAlexW3040705839

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.