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Inferring the drivers of language change using spatial models
Author(s) -
James Burridge,
Tamsin Blaxter
Publication year - 2021
Publication title -
journal of physics complexity
Language(s) - English
Resource type - Journals
ISSN - 2632-072X
DOI - 10.1088/2632-072x/abfa82
Subject(s) - computer science , simple (philosophy) , measure (data warehouse) , spatial change , diffusion , econometrics , cognitive psychology , artificial intelligence , geography , psychology , data mining , mathematics , physical geography , epistemology , philosophy , physics , thermodynamics
Discovering and quantifying the drivers of language change is a major challenge. Hypotheses about causal factors proliferate, but are difficult to rigorously test. Here we ask a simple question: can 20th century changes in English be explained as a consequence of spatial diffusion, or have other processes created bias in favour of certain linguistic forms? Using two of the most comprehensive spatial datasets available, which measure the state of English at the beginning and end of the 20th century, we calibrate a simple spatial model so that, initialised with the early state, it evolves into the later. Our calibrations reveal that while some changes can be explained by diffusion alone, others are clearly the result of substantial asymmetries between variants. We discuss the origins of these asymmetries and, as a by-product, we generate a full spatio–temporal prediction for the spatial evolution of English features over the 20th century, and a prediction of the future.

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