Dependency distance minimization: a diachronic exploration of the effects of sentence length and dependency types

Xueying Liu, Haoran Zhu and Lei Lei ()
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Xueying Liu: Huazhong University of Science and Technology
Haoran Zhu: Huazhong University of Science and Technology
Lei Lei: Shanghai International Studies University

Palgrave Communications, 2022, vol. 9, issue 1, 1-9

Abstract: Abstract Dependency distance is regarded as an index of memory load and a measure of syntactic difficulty. Previous research has found that dependency distance tends to minimize both synchronically and diachronically due to the limited resource of working memory. However, little is known concerning the effects of different dependency types on the dependency distance minimization. In addition, previous studies showed inconsistent results on the anti-minimization of dependency distance in shorter sentences. Hence, a more fine-grained investigation is needed on the diachronic change of dependency distance with shorter sentences such as those of three or four words. To address these issues, this study intends to explore the diachronic change of dependency distance in terms of two variables, i.e., dependency types and sentence length. Results show that anti-minimization does exist in short sentences diachronically, and sentence length has an effect on diachronic dependency distance minimization of dependency types. More importantly, not all dependency types present a decreasing trend, while only nine types of dependency relations are responsible for the dependency distance minimization. Possible explanations for the findings are offered.

Date: 2022
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DOI: 10.1057/s41599-022-01447-3

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