Division of labor in vocabulary structure:insights from corpus analyses

Christiansen, Morten H. and Monaghan, Padraic (2016) Division of labor in vocabulary structure:insights from corpus analyses. Topics in Cognitive Science, 8 (3). pp. 610-624. ISSN 1756-8757

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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.

Item Type:
Journal Article
Journal or Publication Title:
Topics in Cognitive Science
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1702
Subjects:
ID Code:
84606
Deposited By:
Deposited On:
07 Feb 2017 11:04
Refereed?:
Yes
Published?:
Published
Last Modified:
24 Apr 2020 12:15