Linguistic evolution driven by network heterogeneity and the Turing mechanism

TL;DR

This paper models the spatial and network-driven evolution of languages using reaction-diffusion systems, revealing how heterogeneity and the Turing mechanism contribute to linguistic coexistence and pattern formation.

Contribution

It introduces a novel reaction-diffusion framework on heterogeneous networks to explain linguistic coexistence and pattern formation, integrating the Turing mechanism with network heterogeneity.

Findings

Reproduces empirical linguistic coexistence patterns in Spain and Austria.

Shows the role of network heterogeneity and Turing instability in language dynamics.

Demonstrates robustness across different geographical datasets.

Abstract

Given the rapidly evolving landscape of linguistic prevalence, whereby a majority of the world's existing languages are dying out in favor of the adoption of a comparatively fewer set of languages, the factors behind this phenomenon has been the subject of vigorous research. The majority of approaches investigate the temporal evolution of two competing languages in the form of differential equations describing their behavior at large scale. In contrast, relatively few consider the spatial dimension of the problem. Furthermore while much attention has focused on the phenomena of language shift---the adoption of majority languages in lieu of minority ones---relatively less light has been shed on linguistic coexistence, where two or more languages persist in a geographically contiguous region. Here, we study the geographical component of language spread on a discrete medium to monitor the dispersal of language species at a microscopic level. Language dynamics is modeled through a reaction-diffusion system that occurs on a heterogeneous network of contacts based on population flows between urban centers. We show that our framework accurately reproduces empirical linguistic trends driven by a combination of the Turing instability, a mechanism for spontaneous pattern-formation applicable to many natural systems, the heterogeneity of the contact network, and the asymmetries in how people perceive the status of a language. We demonstrate the robustness of our formulation on two datasets corresponding to linguistic coexistence in northern Spain and southern Austria.