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Updated: Jun 8, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Dynamical organization towards consensus in the Axelrod model on complex networks.

Beniamino Guerra1, Julia Poncela, Jesús Gómez-Gardeñes

  • 1Laboratorio sui Sistemi Complessi, Scuola Superiore di Catania, Via San Nullo 5/i, 95123 Catania, Italy.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 28, 2010
PubMed
Summary

This study examines cultural consensus dynamics in the Axelrod model on scale-free networks. It reveals that global consensus doesn't always follow feature-level agreement, highlighting distinct diffusion processes.

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Last Updated: Jun 8, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Area of Science:

  • Sociophysics
  • Computational Social Science
  • Network Science

Background:

  • The Axelrod model simulates cultural trait diffusion and consensus formation.
  • Scale-free networks exhibit complex structures influencing social dynamics.
  • Understanding consensus emergence is key to social dynamics research.

Purpose of the Study:

  • To analyze cultural consensus dynamics within the Axelrod model on scale-free networks.
  • To investigate the spread of culture traits across diverse cultural features.
  • To compare feature-level diffusion with global consensus growth.

Main Methods:

  • Microscopic analysis of the Axelrod model dynamics.
  • Examination of trait diffusion across cultural features.
  • Comparison of feature-level and global consensus formation.
  • Analysis of consensus cluster topology.

Main Results:

  • Microscopic dynamics reveal how culture traits spread across features.
  • Significant differences exist between feature-level diffusion and global consensus growth.
  • Global consensus signals are absent even when most features reach macroscopic consensus.
  • Consensus cluster topology differs at global and feature levels.

Conclusions:

  • Cultural consensus formation is complex and network-dependent.
  • Feature-level consensus does not guarantee global cultural globalization.
  • Network topology plays a crucial role in shaping consensus dynamics.