When dialects collide: how socioeconomic mixing affects language use

Abstract The socioeconomic background of people and how they use standard forms of language are not independent, as demonstrated in various sociolinguistic studies. However, the extent to which these correlations may be influenced by the mixing of people from different socioeconomic classes remains...

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Main Authors: Thomas Louf, José J. Ramasco, David Sánchez, Márton Karsai
Format: Article
Language:English
Published: SpringerOpen 2025-07-01
Series:EPJ Data Science
Subjects:
Online Access:https://doi.org/10.1140/epjds/s13688-025-00563-9
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author Thomas Louf
José J. Ramasco
David Sánchez
Márton Karsai
author_facet Thomas Louf
José J. Ramasco
David Sánchez
Márton Karsai
author_sort Thomas Louf
collection DOAJ
description Abstract The socioeconomic background of people and how they use standard forms of language are not independent, as demonstrated in various sociolinguistic studies. However, the extent to which these correlations may be influenced by the mixing of people from different socioeconomic classes remains relatively unexplored from a quantitative perspective. In this work we leverage geotagged tweets and transferable computational methods to map deviations from standard English across eight UK metropolitan areas. We combine these data with high-resolution income maps to assign a proxy socioeconomic indicator to home-located users. Strikingly, we find a consistent pattern suggesting that the more different socioeconomic classes mix, the less interdependent the frequency of their departures from standard grammar and their income become. Further, we propose an agent-based model of linguistic variety adoption that sheds light on the mechanisms that produce the observations seen in the data.
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spelling doaj-art-83bd348bff4c4a828fd3903b6007f2482025-08-20T03:04:26ZengSpringerOpenEPJ Data Science2193-11272025-07-0114112110.1140/epjds/s13688-025-00563-9When dialects collide: how socioeconomic mixing affects language useThomas Louf0José J. Ramasco1David Sánchez2Márton Karsai3Institute for Cross-Disciplinary Physics and Complex Systems IFISC (UIB-CSIC)Institute for Cross-Disciplinary Physics and Complex Systems IFISC (UIB-CSIC)Institute for Cross-Disciplinary Physics and Complex Systems IFISC (UIB-CSIC)Department of Network and Data Science, Central European UniversityAbstract The socioeconomic background of people and how they use standard forms of language are not independent, as demonstrated in various sociolinguistic studies. However, the extent to which these correlations may be influenced by the mixing of people from different socioeconomic classes remains relatively unexplored from a quantitative perspective. In this work we leverage geotagged tweets and transferable computational methods to map deviations from standard English across eight UK metropolitan areas. We combine these data with high-resolution income maps to assign a proxy socioeconomic indicator to home-located users. Strikingly, we find a consistent pattern suggesting that the more different socioeconomic classes mix, the less interdependent the frequency of their departures from standard grammar and their income become. Further, we propose an agent-based model of linguistic variety adoption that sheds light on the mechanisms that produce the observations seen in the data.https://doi.org/10.1140/epjds/s13688-025-00563-9Computational sociolinguisticsDialectsSocioeconomic statusSocial media dataAgent-based modeling
spellingShingle Thomas Louf
José J. Ramasco
David Sánchez
Márton Karsai
When dialects collide: how socioeconomic mixing affects language use
EPJ Data Science
Computational sociolinguistics
Dialects
Socioeconomic status
Social media data
Agent-based modeling
title When dialects collide: how socioeconomic mixing affects language use
title_full When dialects collide: how socioeconomic mixing affects language use
title_fullStr When dialects collide: how socioeconomic mixing affects language use
title_full_unstemmed When dialects collide: how socioeconomic mixing affects language use
title_short When dialects collide: how socioeconomic mixing affects language use
title_sort when dialects collide how socioeconomic mixing affects language use
topic Computational sociolinguistics
Dialects
Socioeconomic status
Social media data
Agent-based modeling
url https://doi.org/10.1140/epjds/s13688-025-00563-9
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