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Division of labor in vocabulary structure: insights from corpus analyses

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<mark>Journal publication date</mark>07/2016
<mark>Journal</mark>Topics in Cognitive Science
Issue number3
Volume8
Number of pages15
Pages (from-to)610-624
Publication StatusPublished
Early online date24/09/15
<mark>Original language</mark>English

Abstract

Psychologists have used experimental methods to study language for more than a century. However, only with the recent availability of large-scale linguistic databases has a more complete picture begun to emerge of how language is actually used, and what information is available as input to language acquisition. Analyses of such big data have resulted in reappraisals of key assumptions about the nature of language. As an example, we focus on corpus-based research that has shed new light on the arbitrariness of the sign: the longstanding assumption that the relationship between the sound of a word and its meaning is arbitrary. The results reveal a systematic relationship between the sound of a word and its meaning, which is stronger for early acquired words. Moreover, the analyses further uncover a systematic relationship between words and their lexical categoriesnouns and verbs sound differently from each otheraffecting how we learn new words and use them in sentences. Together, these results point to a division of labor between arbitrariness and systematicity in sound-meaning mappings. We conclude by arguing in favor of including big data analyses into the language scientist's methodological toolbox.

Psychologists have used experimental methods to study language for more than a century. However, only with the recent availability of large-scale linguisticdatabases has a more complete picture begun to emerge of how language is actually used and what information is available as input to language acquisition. Analyses of such big data' have resulted in reappraisals of key assumptions about the nature of language, including the arbitrariness of the sign which is the focus on this paper.