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Finding developmental groups in acquisition data: variability-based neighbor clustering


Gries, Stefan; Stoll, Sabine (2009). Finding developmental groups in acquisition data: variability-based neighbor clustering. Journal of Quantitative Linguistics, 16:217-242.

Abstract

This article introduces a quantitative, data-driven method to identify clusters of groups of data points in longitudinal data. We illustrate this method with examples from first-language acquisition research. First, we discuss a variety of shortcomings of current practices in the identification and handling of stages in studies of language acquisition. Second, we explain and exemplify our method, which we refer to as variability-based neighbour clustering, on the basis of mean length of utterance (MLU) values and lexical growth in two different corpora. Third, we discuss the method's advantages and briefly point to further applications both in language acquisition and in diachronic linguistics.

Abstract

This article introduces a quantitative, data-driven method to identify clusters of groups of data points in longitudinal data. We illustrate this method with examples from first-language acquisition research. First, we discuss a variety of shortcomings of current practices in the identification and handling of stages in studies of language acquisition. Second, we explain and exemplify our method, which we refer to as variability-based neighbour clustering, on the basis of mean length of utterance (MLU) values and lexical growth in two different corpora. Third, we discuss the method's advantages and briefly point to further applications both in language acquisition and in diachronic linguistics.

Citations

6 citations in Web of Science®
4 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > English Department
Dewey Decimal Classification:820 English & Old English literatures
Language:English
Date:2009
Deposited On:17 Dec 2013 11:53
Last Modified:21 May 2016 07:36
Publisher:Taylor & Francis
ISSN:0929-6174
Publisher DOI:https://doi.org/10.1080/09296170902975692

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