When Dialects Collide: How Socioeconomic Mixing Affects Language Use
Thomas Louf José J. Ramasco David Sánchez Márton Karsai
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 on a large scale, in seven thousand administrative areas of England and
Wales. We combine these data with high-resolution income maps to assign a proxy
socioeconomic indicator to home-located users. Strikingly, across eight
metropolitan areas 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.