Markov Models for Multi-state Language Change

Abstract

Historical linguistics has witnessed an upsurge in quantitative corpus studies. The bulk of these studies involve the use of regression modelling. We point out a number of potential problems with this approach, and offer an alternative. For a multi-state language change, we propose a Markov model in continuous time. The major advantage of this technique, which has been used in medical contexts, is that it is especially geared towards dealing with time as a variable of interest, while it still allows one to look at the effect of several covariates. In this proof-of-concept article, we look at morphological shifts in preterites in Dutch, from 800AD to 2000AD (n = 14,314). This is a well-researched field, allowing us to investigate the performance of the multi-state Markov model.

Pathways of actualization across regional varieties and the real-time dynamics of syntactic change

“…However, the assumption of unidirectionality has two drawbacks. First, the trajectory of change may not always be entirely straightforward or unidirectional; rather, variation can be pervasive and functional, oscillating throughout history (Norde, 2009;Van de Velde & De Smet, 2021: 3), and a synchronic snapshot may prove misleading if it has been captured at an oscillating moment (Van de Velde, 2017). Second, even if grammaticalization can more often than not be assumed to be unidirectional, not all instances of grammatical change constitute cases of grammaticalization, and these other types of changes are not necessarily unidirectional (cf.…”