Language variation and change: A communicative perspective
Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, DGfS 2020, Hamburg, 2020.
It is widely acknowledged that language use and language structure are closely interlinked, linguistic structure emerging from language use (Bybee & Hopper 2001). Language use, in turn, is characterized by variation; in fact, speakers’ ability to adapt to changing contexts is a prerequisite for language to be functional (Weinreich et al. 1968).
Taking the perspective of rational communication, in my talk I will revisit some core questions of diachronic linguistic change: Why does a change happen? Which features are involved in change? How does change proceed? What are the eff ects of change? Recent work on online human language use reveals that speakers try to optimize their linguistic productions by encoding their messages with uniform information density (see Crocker et al. 2016 for an overview). Here, a major determinant in linguistic choice is predictability in context. Predictability in context is commonly represented by information content measured in bits (Shannon information): The more predictable a linguistic unit (e.g. word) is in a given context, the fewer bits are needed for encoding and the shorter its linguistic encoding may be (and vice versa, the more “surprising” a unit is in a given context, the more bits are needed for encoding and the more explicit its encoding tends to be). In this view, one major function of linguistic variation is to modulate information content so as to optimize message transmission.
In my talk, I apply this perspective to diachronic linguistic change. I show that speakers’ continuous adaptation to changing contextual conditions pushes towards linguistic innovation and results in temporary, high levels of expressivity, but the concern for maintaining communicative function pulls towards convergence and results in conventionalization. The diachronic scenario I discuss is mid-term change (200–250 years) in English in the late Modern period, focusing on the discourse domain of science (Degaetano-Ortlieb & Teich 2019). In terms of methods, I use computational language models to estimate predictability in context; and to assess diachronic change, I apply selected measures of information content, including entropy and surprisal.