2022-04-14, 09:00–09:30 (Europe/Vienna), Room 3
The English language has become pervasive in education (Gerards, 2017; NOG, 2018; SLO, 2019) and society (Gerritsen et al., 2000; Gerritsen & Nickerson, 2004; van Meurs et al., 2006) in the Netherlands. Moreover, it has become an online lingua franca (Crystal, 2001, 2011; Warschauer et al., 2010) and “typical of international chat culture” (Hilte, 2019: 66). This perceived ‘intrusion’ of English into Dutch has caused concerns (Appel & Noordervliet, 2019; SCP, 2019). Although English is a manifest aspect of oral youth language, as reflected in online written messages, it has in no way replaced the Dutch language (Verheijen et al., 2018). This paper presents a large-scale corpus analysis, delving into the use of English in informal computer-mediated communication by Dutch youths. From these social media messages, consisting of 392,169 words in total, all code-mixings with English were extracted and manually coded in relation to their linguistic form and communicative function. Code-mixing refers to the use of elements from a second or foreign language (in this case, English) in one’s first language (here, Dutch). We studied both the amount and manner of code-mixing in our corpus. It contained 7,528 English elements, divided into the categories of words, interjections, textisms (i.e. text-messaging style orthographic deviations from the spelling norms, typical of ‘digi-talk’; Verheijen, 2017), phrases, and sentences.
We argue that the concept of ‘manifold code-mixing’ is necessary to truly comprehend the complexity and multifunctionality of code-mixing. Manifold code-mixing consists of four pathways: discourse framing (the use of English discourse markers, such as interjections and textisms, in dialogue), insertion (the input of English single words, mainly content words, within Dutch utterances), alternation (the switch between Dutch and English phrases and full sentences, including function words and English syntax), and integration (the adaptation of English to the Dutch language on different linguistic levels, morphological and/or orthographic). These different modes of code-mixing each have their own properties and driving forces, relate to the SUPER-functions of textisms (speechlike, understandable, playful, expressive, reduced; Verheijen, 2018), and reveal Dutch youths’ high proficiency in English. We have applied this distinction between the four pathways to the coded English elements in our corpus of Dutch youths’ CMC. Manifold code-mixing transcends mere borrowability patterns and presents a sophisticated sociolinguistic analysis of code-mixing.
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