On an Interaction Model of General Language Change

TL;DR

This paper develops a mathematical interaction model of language change, analyzing its long-term behavior and demonstrating how data can predict whether language change will be complete or reversible.

Contribution

It introduces a novel interaction model based on the SIR framework for language change and provides methods to analyze and predict long-term language evolution.

Findings

Proves the absence of periodic orbits in the model

Shows convergence to critical points determines long-term behavior

Demonstrates data-fitting can predict language change outcomes

Abstract

In the following article, we construct an interaction model (a variant of the SIR-model) of general language change. In the context of language change it is desirable to deduce the long-term behaviour of the corresponding dynamical system (for example to decide if complete of reversible language change are going to happen). We analyse this dynamical system by first proving non-existence of periodic orbits and then invoking the Poincar\'{e}-Bendixson theorem to show convergence to critical points only. Non-existence of periodic orbits is established by contradiction in showing that the average position of a potential periodic orbit must coincide with a certain critical point $C$ which cannot be encircled by the flow of the dynamical system so that the average position would be pulled to that side. Thus the long-term behaviour of the model for any given initial constellation of speakers depends only on four interaction parameters and can be easily analysed by looking at the four critical points. Subsequent numerical analysis of real data on language change is used to justify the relevance of the constructed model for the practicing quantitative linguist. We show how data-fitting methods can be used to determine the four interaction parameters and predict from them the long-term behaviour of the system, i.e. if complete language change or reversible language change will take place.