Saved in:
Bibliographic Details
Main Author: Burridge, James
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2512.17668
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911328107495424
author Burridge, James
author_facet Burridge, James
contents Is it possible to develop a `physics of language' which can explain the spatial, temporal and social patterns we see, and which can predict future change like we forecast the weather? Such a theory is likely to involve ideas from statistical physics. A substantial literature already applies these ideas to language. However, we lack a model which can match the spatial-temporal detail of historical changes at the level of individual linguistic features, and which offers a principled mechanism to predict the future. Here we present a statistical field theory for the evolution of linguistic variables which takes steps to fill this gap. Linguistic variant frequencies are represented as a stochastic state field with spatial interaction and social conformity, coupled to a latent bias field with Onsager Machlup action that reduces overfitting to data. We derive parameter inference procedures and demonstrate them using examples of large-scale dialect survey data from the twentieth century United States. The bias field has a characteristic half-life, which determines the horizon over which linguistic change can be predicted. Inferred model parameters provide evidence for surface-tension-driven coarsening of dialect regions, with population-density gradients exerting systematic forces on interfaces.
format Preprint
id arxiv_https___arxiv_org_abs_2512_17668
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Statistical field theory for dialectology
Burridge, James
Physics and Society
Is it possible to develop a `physics of language' which can explain the spatial, temporal and social patterns we see, and which can predict future change like we forecast the weather? Such a theory is likely to involve ideas from statistical physics. A substantial literature already applies these ideas to language. However, we lack a model which can match the spatial-temporal detail of historical changes at the level of individual linguistic features, and which offers a principled mechanism to predict the future. Here we present a statistical field theory for the evolution of linguistic variables which takes steps to fill this gap. Linguistic variant frequencies are represented as a stochastic state field with spatial interaction and social conformity, coupled to a latent bias field with Onsager Machlup action that reduces overfitting to data. We derive parameter inference procedures and demonstrate them using examples of large-scale dialect survey data from the twentieth century United States. The bias field has a characteristic half-life, which determines the horizon over which linguistic change can be predicted. Inferred model parameters provide evidence for surface-tension-driven coarsening of dialect regions, with population-density gradients exerting systematic forces on interfaces.
title Statistical field theory for dialectology
topic Physics and Society
url https://arxiv.org/abs/2512.17668