A stochastic opinion dynamics model with domain size dependent dynamic evolution

TL;DR

This paper presents a stochastic opinion dynamics model in one dimension, revealing a phase transition in exit probability and unique coarsening behavior, suggesting a new universality class in dynamical systems.

Contribution

The paper introduces a novel stochastic opinion model with domain size-dependent flip probabilities, identifying a phase transition and a new universality class for persistence.

Findings

Phase transition observed in exit probability in the $\delta - x$ plane.

Conventional scaling only at the phase transition point $\delta=1$.

Model belongs to a new dynamical universality class for persistence.

Abstract

We introduce a stochastic model of binary opinion dynamics in one dimension. The binary opinions $\pm 1$ are analogous to up and down Ising spins and in the equivalent spin system, only the spins at the domain boundary can flip. The probability that a spin at the boundary is up is taken as $P_{up} = \frac {s_{up}} {s_{up} + \delta s_{down}}$ where $s_{up} (s_{down})$ denotes the size of the domain with up (down) spins neighbouring it. With $x$ fraction of up spins initially, a phase transition is observed in terms of the exit probability and the phase boundary is obtained in the $\delta -x$ plane. In addition, we investigate the coarsening behaviour starting from a completely random state; conventional scaling is observed only at the phase transition point $\delta = 1$. The scaling behaviour is compared to other dynamical phenomena; the model apparently belongs to a new dynamical universility class as far as persistence is concerned although the dynamical exponent, equal to one, is identical to a similar model with no stochasticity.