Emergence of hierarchy in networked endorsement dynamics

Abstract

Hierarchies structure the lives of many social animals, including humans. We propose a generative model of time-varying networks in which endorsements between individuals give rise to enduring hierarchies. For several network-based ranking functions, our model possesses a distinct, analytically tractable, critical transition between egalitarian and hierarchical states. We also use our model to explore 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. Overall, our model enables data-informed modeling of hierarchical networks in social and biological systems.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 13, 2021
Source ID
10.1073/pnas.2015188118

Entities

People

  • Daniel B. Larremore
  • Mari Kawakatsu
  • Nicole Eikmeier
  • Philip S Chodrow

Organizations

  • Air Force Office of Scientific Research
  • Army Research Office
  • Grinnell College
  • Massachusetts Institute of Technology
  • National Science Foundation
  • Princeton University
  • University of California
  • University of Colorado Boulder

Tags

Fields of Study

  • Computer science

Readers

  • Educational Psychology
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy