On Spatial Consensus Formation: Is the Sznajd Model Different from a Voter Model?

TL;DR

This paper demonstrates that the one-dimensional Sznajd Model for opinion consensus can be exactly reformulated as a voter model based on second-nearest neighbors, revealing a phase transition influenced by a bias parameter and update rules.

Contribution

The authors show the equivalence between the Sznajd Model and a linear voter model, introducing a bias parameter and analyzing the effects of update schemes on consensus dynamics.

Findings

SM and VM exhibit identical behavior in key metrics

The bias parameter $\sigma$ explains phase transitions in SM

Different update rules lead to additional attractors

Abstract

In this paper, we investigate the so-called ``Sznajd Model'' (SM) in one dimension, which is a simple cellular automata approach to consensus formation among two opposite opinions (described by spin up or down). To elucidate the SM dynamics, we first provide results of computer simulations for the spatio-temporal evolution of the opinion distribution $L(t)$, the evolution of magnetization $m(t)$, the distribution of decision times $P(\tau)$ and relaxation times $P(\mu)$. In the main part of the paper, it is shown that the SM can be completely reformulated in terms of a linear VM, where the transition rates towards a given opinion are directly proportional to frequency of the respective opinion of the second-nearest neighbors (no matter what the nearest neighbors are). So, the SM dynamics can be reduced to one rule, ``Just follow your second-nearest neighbor''. The equivalence is demonstrated by extensive computer simulations that show the same behavior between SM and VM in terms of $L(t)$, $m(t)$, $P(\tau)$, $P(\mu)$, and the final attractor statistics. The reformulation of the SM in terms of a VM involves a new parameter $\sigma$, to bias between anti- and ferromagnetic decisions in the case of frustration. We show that $\sigma$ plays a crucial role in explaining the phase transition observed in SM. We further explore the role of synchronous versus asynchronous update rules on the intermediate dynamics and the final attractors. Compared to the original SM, we find three additional attractors, two of them related to an asymmetric coexistence between the opposite opinions.