Super happy to share that, after two great years @chub-fbk.bsky.social, I've just joined @uc3m.es and the GISC as an assistant prof in applied maths :)))

We show analytically that increased mixing does make different classes converge on their dialect usage. And since it's an ABM, we can simulate agents moving around according to actual mobility patterns, and again we found one of these nice straight lines we all love 🫶

That's why we proposed some basic mechanisms that could explain this, in the form of an agent-based model. Use of a variety depends on how prestigious the standard form is (s), how much the poorer class prefers non-standard (q1), and how much the richer prefer standard (q2).

This was really surprising to us, so we had to understand where these differences could be coming from! That's when we thought of looking at how much people of different classes mix in each of these cities. And what we found is this very nice line 🔽

This gives a nice proxy for the tendency of Twitter users to use non-standard English. And what we found were smaller correlations than we expected, but more crucially, widely different ones from one metropolitan area of England to the other.

If you still had any doubt this was worth sharing