Why do we say them when we know it should be they? Twitter as a resource for investigating nonstandard syntactic variation in The Netherlands

Abstract Two Twitter-based corpus studies are reported to account for the increasing preference in The Netherlands for the stigmatized subject use of the object pronoun hun ‘them.’ Twitter data were collected to obtain a sufficient number of hun -tokens, but also to investigate the validity of two hypotheses on the preference for hun , this is, that subject- hun is a contrast profiler which thrives in contexts of evaluation and qualification, and that subject- hun is propelled by its dynamic social meaning, being a tool for nonposh and streetwise self-stylization. Although the latter is not no... Mehr ...

Verfasser: Grondelaers, Stefan
van Hout, Roeland
van Halteren, Hans
Veerbeek, Esther
Dokumenttyp: Artikel
Erscheinungsdatum: 2023
Reihe/Periodikum: Language Variation and Change ; volume 35, issue 2, page 223-245 ; ISSN 0954-3945 1469-8021
Verlag/Hrsg.: Cambridge University Press (CUP)
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27628280
Datenquelle: BASE; Originalkatalog
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Link(s) : http://dx.doi.org/10.1017/s0954394523000121

Abstract Two Twitter-based corpus studies are reported to account for the increasing preference in The Netherlands for the stigmatized subject use of the object pronoun hun ‘them.’ Twitter data were collected to obtain a sufficient number of hun -tokens, but also to investigate the validity of two hypotheses on the preference for hun , this is, that subject- hun is a contrast profiler which thrives in contexts of evaluation and qualification, and that subject- hun is propelled by its dynamic social meaning, being a tool for nonposh and streetwise self-stylization. Although the latter is not normally a predictor included in regression analyses of constructional choice, it turns out that expressively spruced up tweets with vivid contrast profiling are the prime biotope of subject- hun . Along the way, this paper reviews the potential of Twitter data for the reconciliation of macro-big-data analysis with micro-sociolinguistic focus, but it also reports and attempts to remedy three concerns.