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

Liu, Xueying; Zhu, Haoran; Lei, Lei

doi:10.1057/s41599-022-01447-3

Cited by 6 publications

(1 citation statement)

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“…Academic writing in a second language (L2) poses many challenges for L2 learners. One important aspect of academic writing quality is syntactic complexity ( Lu, 2011 ), which can be measured by dependency distance (DD)—the linear distance between syntactically related words in a sentence ( Tesnière, 1959 ; Liu, 2007 , 2008 ; Hudson, 2010 ; Liu et al, 2017 , 2022 ). In their exploration of DD, researchers have also examined dependency direction ( Liu et al, 2009 ; Liu, 2010 ; Jiang and Liu, 2015 ; Wang and Liu, 2017 ; Fan and Jiang, 2019 )—a concept that delineates the positional relationship between a governor and its dependent within syntactically connected word pairs, specifically whether the governor appears after or before its dependent.…”

Section: Introductionmentioning

confidence: 99%

Language transfer in L2 academic writings: a dependency grammar approach

Bi,

Tan

2024

Front. Psychol.

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Dependency distance (DD) is an important factor in language processing and can affect the ease with which a sentence is understood. Previous studies have investigated the role of DD in L2 writing, but little is known about how the native language influences DD in L2 academic writing. This study is probably the first one that investigates, though a large dataset of over 400 million words, whether the native language of L2 writers influences the DD in their academic writings. Using a dataset of over 2.2 million abstracts of articles downloaded from Scopus in the fields of Arts & Humanities and Social Sciences, the study analyzes the DD patterns, parsed by the latest version of the syntactic parser Stanford Corenlp 4.5.5, in the academic writing of L2 learners from different language backgrounds. It is found that native languages influence the DD of English L2 academic writings. When the mean dependency distance (MDD) of native languages is much longer than that of native English, the MDD of their English L2 academic writings will be much longer than that of English native academic writings. The findings of this study will deepen our insights into the influence of native language transfer on L2 academic writing, potentially shaping pedagogical strategies in L2 academic writing education.

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Section: Introductionmentioning

confidence: 99%

Language transfer in L2 academic writings: a dependency grammar approach

Bi,

Tan

2024

Front. Psychol.

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The diachronic change of research article abstract difficulty across disciplines: a cognitive information-theoretic approach

Xin

Wei

2023

Humanit Soc Sci Commun

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Text difficulty refers to the ease with which a text can be read and understood, and the difficulty of research article abstracts has long been a hot topic. Previous studies have found that research article abstracts are difficult to read in general and that abstracts have gradually become more and more difficult. However, the widely used measurements, such as FRE and SMOG, have long been criticized in that they use only simplistic and surface-level indicators as proxies for complex cognitive processes of reading, and the sophisticated cognitive theory and Natural Language Processing/machine learning-based methods seem not that easy to use and interpret. A theoretically sound and methodologically neat measurement of text difficulty should be called for. Besides, the diachronic changes of abstract difficulty across disciplines have been under-researched. To address these issues, this study adopted a cognitive information-theoretic approach to investigate the diachronic change of text difficulty of research article abstracts across the areas of natural sciences, social sciences, and humanities. 1890 abstracts were sampled over a period of 21 years, and two indexes, i.e. entropy from information theory and mean dependency distance from cognitive science, were employed for the calculation of cognitive encoding/decoding difficulty. The results show that in general, the cognitive encoding difficulty of abstracts has been increasing in the past two decades, while the cognitive decoding difficulty of abstracts has been decreasing. Regarding the disciplinary variations, the humanities show no significant diachronic change in encoding difficulty, and the social sciences show no significant diachronic change in decoding difficulty. These phenomena can be attributed to the traits of abstracts, the nature of academic knowledge, the cognitive mechanism in human languages and the features of different disciplines. This study has implications for the innovations in theories and methods of measurement of text difficulty, as well as an in-depth understanding of the disciplinary variations in academic writing and the essence of research article abstracts for research article writers, readers, the scientific community, and academic publishers.

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Probability distribution of dependency distance and dependency type in translational language

Fan,

Jiang

2023

Humanit Soc Sci Commun

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As a “third code”, translational language attracts considerable attention in linguistics research due to its distinctive features. Adopting the quantitative linguistic approach, the current study examines its features by investigating the mean dependency distance (MDD), as well as the probability distribution of the individual dependency distances (DDs) and distribution of a high-frequency dependency type in translational language. The MDD and the distributions were tested in a self-built corpus which contains parallel and comparable language materials in both Chinese-English and English-Chinese translations. The results show that: (1) compared with source texts and native texts, translated texts in both translation directions yield an MDD in between; (2) both the distribution of DDs and that of the dependency type nsubj follow the Zipf-Alekseev distribution in translated texts, as in source texts and native texts; (3) the in-between feature is further confirmed by parameters a and b in Chinese-English translation materials when fitting the distribution of DDs to Zipf-Alekseev distribution; (4) translational texts in both directions show higher a and lower b than their source and native texts when fitting the DD Distribution of dependency type nsubj to Zipf-Alekseev distribution. These findings suggest that, on the one hand, dependency distance minimization (DDM) occurs in translational language, which is consistent with native language and reflects a general tendency of natural languages to reduce cognitive load; on the other hand, translational language presents distinctive feature in nsubj type, but in most cases, it is subject to the gravitational pull of both source and target language systems, exhibiting a “compromise” feature in between. The current study highlights the contribution of syntactic quantitative methods to deeper understanding of the complexity of translational language and its cognitive underpinnings.

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

Cited by 6 publications

References 48 publications

Language transfer in L2 academic writings: a dependency grammar approach

Language transfer in L2 academic writings: a dependency grammar approach

The diachronic change of research article abstract difficulty across disciplines: a cognitive information-theoretic approach

Probability distribution of dependency distance and dependency type in translational language

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