https://doi.org/10.1140/epjds/s13688-025-00563-9
Research
When dialects collide: how socioeconomic mixing affects language use
1
Institute for Cross-Disciplinary Physics and Complex Systems IFISC (UIB-CSIC), Palma de Mallorca, Spain
2
Fondazione Bruno Kessler, Povo (TN), Italy
3
Department of Network and Data Science, Central European University, Vienna, Austria
4
National Laboratory for Health Security, HUN-REN Alfréd Rényi Institute of Mathematics, Budapest, Hungary
a
tlouf@fbk.eu
b
karsaim@ceu.edu
Received:
21
February
2025
Accepted:
6
June
2025
Published online:
10
July
2025
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.
Key words: Computational sociolinguistics / Dialects / Socioeconomic status / Social media data / Agent-based modeling
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1140/epjds/s13688-025-00563-9.
© The Author(s) 2025
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