Distribution of sentence length and dependency distance in children's compositions: Characteristics of natural language and variations in language development

This study analyzed the distribution of the sentence length and mean of dependency distances (MDD) in Japanese sentences, comparing data from random sources with that obtained from children's compositions, and identifying changes in distribution according to grade level. Findings reveal that th...

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Bibliographic Details
Published in:F1000 research 2023, Vol.12, p.379-379
Main Author: Imada, Mizuho
Format: Article
Language:eng ; jpn
Subjects:
Child
children's compositions
dependency distance
Depressive Disorder, Major
eng
generalized linear mixed model
Humans
Language
Language Development
probability distribution
sentence length
文長
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Summary:This study analyzed the distribution of the sentence length and mean of dependency distances (MDD) in Japanese sentences, comparing data from random sources with that obtained from children's compositions, and identifying changes in distribution according to grade level. Findings reveal that the sentence length in random data is well suited to a geometric distribution, whereas MDD is well suited to a lognormal distribution. In contrast, data from children's compositions show a shift in the distribution of the number of clauses from a lognormal to a gamma distribution, depending on the school year, with MDD suiting a gamma distribution. Mean MDD increases exponentially with the logarithm of the number of clauses in random data, while it increases linearly in composition data, thus generally supporting previous findings that dependency distances are optimized in natural language. However, MDDs exhibit non-monotonic changes with grades, suggesting the complexity of children's language development.
ISSN:2046-1402
2046-1402
DOI:10.12688/f1000research.132383.1