Dynamical organization towards consensus in the Axelrod model on complex networks

TL;DR

This paper investigates how cultural traits spread and reach consensus in the Axelrod model on complex networks, revealing differences between feature-level diffusion and global consensus, and analyzing the topology of consensus clusters.

Contribution

It provides a microscopic analysis of cultural trait diffusion and compares feature-level and global consensus processes in the Axelrod model on scale-free networks.

Findings

Differences between feature-level diffusion and global consensus growth.

Most features reach macroscopic consensus without global globalization.

Topology of consensus clusters analyzed at both global and feature levels.

Abstract

We analyze the dynamics toward cultural consensus in the Axelrod model on scale-free networks. By looking at the microscopic dynamics of the model, we are able to show how culture traits spread across different cultural features. We compare the diffusion at the level of cultural features to the growth of cultural consensus at the global level, finding important differences between these two processes. In particular, we show that even when most of the cultural features have reached macroscopic consensus, there are still no signals of globalization. Finally, we analyze the topology of consensus clusters both for global culture and at the feature level of representation.