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Division of labor in vocabulary structure: insights from corpus analyses

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Division of labor in vocabulary structure : insights from corpus analyses. / Christiansen, Morten H.; Monaghan, Padraic.

In: Topics in Cognitive Science, Vol. 8, No. 3, 07.2016, p. 610-624.

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Christiansen, MH & Monaghan, P 2016, 'Division of labor in vocabulary structure: insights from corpus analyses', Topics in Cognitive Science, vol. 8, no. 3, pp. 610-624. https://doi.org/10.1111/tops.12164

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Christiansen, Morten H. ; Monaghan, Padraic. / Division of labor in vocabulary structure : insights from corpus analyses. In: Topics in Cognitive Science. 2016 ; Vol. 8, No. 3. pp. 610-624.

Bibtex

@article{049f984009a3449fa4d69490a50e5b89,
title = "Division of labor in vocabulary structure: insights from corpus analyses",
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.",
keywords = "Vocabulary, Corpus analysis, Form-meaning mappings, Arbitrariness, Systematicity, Lexical categories, Sound symbolism, Big data, PHONOTACTIC PROBABILITY, WORDS, MODELS, ENGLISH, CATEGORIZATION, ACQUISITION, SOUND",
author = "Christiansen, {Morten H.} and Padraic Monaghan",
year = "2016",
month = jul
doi = "10.1111/tops.12164",
language = "English",
volume = "8",
pages = "610--624",
journal = "Topics in Cognitive Science",
issn = "1756-8757",
publisher = "Blackwell-Wiley",
number = "3",

}

RIS

TY - JOUR

T1 - Division of labor in vocabulary structure

T2 - insights from corpus analyses

AU - Christiansen, Morten H.

AU - Monaghan, Padraic

PY - 2016/7

Y1 - 2016/7

N2 - 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.

AB - 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.

KW - Vocabulary

KW - Corpus analysis

KW - Form-meaning mappings

KW - Arbitrariness

KW - Systematicity

KW - Lexical categories

KW - Sound symbolism

KW - Big data

KW - PHONOTACTIC PROBABILITY

KW - WORDS

KW - MODELS

KW - ENGLISH

KW - CATEGORIZATION

KW - ACQUISITION

KW - SOUND

U2 - 10.1111/tops.12164

DO - 10.1111/tops.12164

M3 - Journal article

VL - 8

SP - 610

EP - 624

JO - Topics in Cognitive Science

JF - Topics in Cognitive Science

SN - 1756-8757

IS - 3

ER -