Functional shortcuts in language co-occurrence networks

Human language contains regular syntactic structures and grammatical patterns that should be detectable in their co-occurence networks. However, most standard complex network measures can hardly differentiate between co-occurence networks built from an empirical corpus and a body of scrambled text....

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Main Authors: Goh, Woon Peng, Luke, Kang-Kwong, Cheong, Siew Ann
Other Authors: Ferrara, Emilio
Format: Journal Article
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/89694
http://hdl.handle.net/10220/46351
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author Goh, Woon Peng
Luke, Kang-Kwong
Cheong, Siew Ann
author2 Ferrara, Emilio
author_facet Ferrara, Emilio
Goh, Woon Peng
Luke, Kang-Kwong
Cheong, Siew Ann
author_sort Goh, Woon Peng
collection NTU
description Human language contains regular syntactic structures and grammatical patterns that should be detectable in their co-occurence networks. However, most standard complex network measures can hardly differentiate between co-occurence networks built from an empirical corpus and a body of scrambled text. In this work, we employ a motif extraction procedure to show that empirical networks have much greater motif densities. We demonstrate that motifs function as efficient and effective shortcuts in language networks, potentially explaining why we are able to generate and decipher language expressions so rapidly. Finally we suggest a link between motifs and constructions in Construction Grammar as well as speculate on the mechanisms behind the emergence of constructions in the early stages of language acquisition.
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spelling ntu-10356/896942020-10-08T06:25:57Z Functional shortcuts in language co-occurrence networks Goh, Woon Peng Luke, Kang-Kwong Cheong, Siew Ann Ferrara, Emilio School of Humanities School of Physical and Mathematical Sciences Interdisciplinary Graduate School (IGS) Complexity Institute Human Language Co-occurence Networks DRNTU::Humanities::Language Human language contains regular syntactic structures and grammatical patterns that should be detectable in their co-occurence networks. However, most standard complex network measures can hardly differentiate between co-occurence networks built from an empirical corpus and a body of scrambled text. In this work, we employ a motif extraction procedure to show that empirical networks have much greater motif densities. We demonstrate that motifs function as efficient and effective shortcuts in language networks, potentially explaining why we are able to generate and decipher language expressions so rapidly. Finally we suggest a link between motifs and constructions in Construction Grammar as well as speculate on the mechanisms behind the emergence of constructions in the early stages of language acquisition. Published version 2018-10-17T04:20:45Z 2019-12-06T17:31:21Z 2018-10-17T04:20:45Z 2019-12-06T17:31:21Z 2018 Journal Article Goh, W. P., Luke, K.-K., & Cheong, S. A. (2018). Functional shortcuts in language co-occurrence networks. PLOS ONE, 13(9), e0203025-. doi:10.1371/journal.pone.0203025 https://hdl.handle.net/10356/89694 http://hdl.handle.net/10220/46351 10.1371/journal.pone.0203025 en PLOS ONE © 2018 Goh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 18 p. application/pdf
spellingShingle Human Language
Co-occurence Networks
DRNTU::Humanities::Language
Goh, Woon Peng
Luke, Kang-Kwong
Cheong, Siew Ann
Functional shortcuts in language co-occurrence networks
title Functional shortcuts in language co-occurrence networks
title_full Functional shortcuts in language co-occurrence networks
title_fullStr Functional shortcuts in language co-occurrence networks
title_full_unstemmed Functional shortcuts in language co-occurrence networks
title_short Functional shortcuts in language co-occurrence networks
title_sort functional shortcuts in language co occurrence networks
topic Human Language
Co-occurence Networks
DRNTU::Humanities::Language
url https://hdl.handle.net/10356/89694
http://hdl.handle.net/10220/46351
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