Surfing the fourth wave. Social meaning as a rapid diffusion determinant in experiments and tweets

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Beschrijving

Since Eckert’s (2012) seminal classification of social meaning treatment in a First, Second, and Third Wave, sociolinguists have become aware that speakers are more than “token-bundles of demographic characteristics” (p. 99), and that social meaning making is an agentive, dynamic and highly contextualized process, which is not conducive to rigid quantitative analysis.
In this paper, however, I propose a “Fourth Wave” approach which quantifies contextualized social meaning as a predictor of two recent diffusions in Netherlandic Dutch.
Vocal fry is a type of phonation (caused by the slackening of the vocal cords) which sounds like the sizzling of frying bacon. Vocal fry is well-known and well-theorized in the US/UK, but in The Netherlands, it was linguistically “discovered” only in 2019; to date, there have been no sound empirical accounts of the reasons for its Dutch diffusion. I present recent corpus and speaker evaluation data to demonstrate that vocal fry is associated with a number of identifiable social meanings (nonchalance in formal contexts, and dynamism in engaged contexts) which plausibly determine its diffusion.
In a second case study, I focus on a somewhat older innovation, the stigmatized non-standard use of the object pronoun hun “them” as a subject. I collected Twitter data to obtain a sufficient number of tokens of subject-hun, but also to investigate the validity of two hypotheses, viz. (1) that subject-hun is a “vivid contrast” profiler which thrives in contexts of evaluation and qualification, and (2) that it is propelled by the cool prestige that has been confirmed as a social meaning correlate of many other diffusions (also in the UK, see Stuart-Smith et al. 2013 for an overview).
If we want to demonstrate that the diffusion of hun is co-determined by cool prestige, it is essential that we can compare such social meaning propellers to grammar-internal predictors in one encompassing analysis. Such an integrated analysis presupposes that we can infer social meaning predictors from production data. For this ambition too, Twitter fosters possibilities that standard corpora do not offer.
On a theoretical note, my paper is a plea for an inclusive laboratory sociolinguistics, which recognizes the crucial importance of both social and functional meaning triggers in diffusion processes.
Periode11 mei 2023
Gehouden opQueen Mary, University of London, Verenigd Koninkrijk
Mate van erkenningInternationaal