That’s Cool. Computational Sociolinguistic Methods for Investigating Individual Lexico-grammatical Variation

Abstract

The present study deals with variation in the use of lexico-grammatical patterns and emphasizes the need to embrace individual variation. Targeting the pattern that’s adj (as in that’s right, that’s nice or that’s okay) as a case study, we use a tailor-made Python script to systematically retrieve grammatical and semantic information about all instances of this construction in BNC2014 as well as sociolinguistic information enabling us to study social and individual lexico-grammatical variation among speakers who have used this pattern. The dataset amounts to 4,394 tokens produced by 445 speakers using 159 adjective types in 931 conversations. Using detailed descriptive statistics and mixed-effects regression models, we show that while the choice of some adjectives is partly determined by social variables, situational and especially individual variation is rampant overall. Adopting a cognitive-linguistic perspective and relying on the notion of entrenchment, we interpret these findings as reflecting individual speakers' routines. We argue that computational sociolinguistics is in an ideal position to contribute to the data-driven investigation of individual lexico-grammatical variation and encourage computational sociolinguists to grab this opportunity. For the routines of individual speakers ultimately both underlie and compromise systematic social variation and trigger and steer well-known types of language change including grammaticalization, pragmaticalization and change by invited inference.

Computational sociophonetics using automatic speech recognition

“…For example, written data from social media (e.g. Facebook and Twitter posts, Reddit forums) has been used to study variation in English phonology (Eisenstein, 2015), morphology (Illbury, 2020), syntax (Dunn, 2019; Johannsen et al., 2015; Szmrecsanyi et al., 2019) and lexicon (Baker, 2012; Bamman et al., 2014; Eisenstein et al., 2014; Grieve et al., 2018, 2019; Hovy & Johannsen, 2016; Huang et al., 2016; Schmid et al., 2021). Automatisation entails data collection by scraping it from the Internet (or using optical character recognition for printed documents) and then extracting patterns (e.g.…”

A social turn for Construction Grammar: double modals on British Twitter

“…However, recent developments in observational linguistic methodology, especially corpus-based computational sociolinguistics (Dunn 2018;Schmid et al 2021;Grieve et al 2023), have begun to lessen these empirical obstacles, allowing us to study a range of dialect constructions, including the rarest and most localised ones, through a corpus-based approach that samples informal written data at scale from online sources, especially social media. By drawing on a computational sociolinguistic methodology, in this article, we aim to encourage the development of CxG into a cognitive sociolinguistic theory.…”