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Constrained language use in Finnish: A corpus-driven approach

Published online by Cambridge University Press:  13 April 2020

Ilmari Ivaska  and
Silvia Bernardini
Ilmari Ivaska*
Affiliation:
Department of Finnish and Finno-Ugric Languages, FI-20014, University of Turku, Finland
Silvia Bernardini*
Affiliation:
Department of Interpreting and Translation, University of Bologna, Corso della Repubblica 136, 47121Forlì (FC), Italy
*
Emails for correspondence: [email protected] and [email protected]
Emails for correspondence: [email protected] and [email protected]
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Abstract

It has been suggested that second languages and translated languages are constrained by an interplay of several linguistic systems. This paper reports on a data-driven quantitative study on constrained Finnish. We detect linguistic phenomena that distinguish constrained from non-constrained Finnish across constrained varieties, first/source languages, and registers. Implementing a two-phase method, we first detect key quantitative differences of syntactically defined POS bigrams between each variety-, language-pair- and register-specific constrained dataset and its non-constrained counterpart, using Boruta feature selection. We then use the results as variables in a Multi-dimensional Analysis. The results show that both nominal complexity and verbal/clausal complexity distinguish constrained from non-constrained Finnish. These differences interact with both type of constraint and register: the constrained varieties are less sensitive to register differences, and this tendency is more pronounced in learner Finnish than in translated Finnish. Leaving out any of these variables from the analysis would blur our view of this multi-faceted phenomenon.

Keywords

constrained language usecorpus-based variationist linguisticsdata-driven approachFinnishkeyness analysisMulti-dimensional Analysissecond language acquisitiontranslation studies
Type
Research Article
Information
Nordic Journal of Linguistics , Volume 43 , Issue 1 , May 2020 , pp. 33 - 57
Copyright
© Cambridge University Press 2020

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