A dependency-based machine learning approach to the identification of research topics: a case in COVID-19 studies

Zhu, Haoran; Lei, Lei

doi:10.1108/lht-01-2021-0051

Cited by 17 publications

(11 citation statements)

References 41 publications

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“…Therefore, future research may consider employing automatic algorithms to extract topics. For example, a dependency-based machine learning approach can be used to identify research topics ( Zhu and Lei, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Trends and hot topics in linguistics studies from 2011 to 2021: A bibliometric analysis of highly cited papers

Song

Zhang²

2023

Front. Psychol.

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High citations most often characterize quality research that reflects the foci of the discipline. This study aims to spotlight the most recent hot topics and the trends looming from the highly cited papers (HCPs) in Web of Science category of linguistics and language & linguistics with bibliometric analysis. The bibliometric information of the 143 HCPs based on Essential Citation Indicators was retrieved and used to identify and analyze influential contributors at the levels of journals, authors, and countries. The most frequently explored topics were identified by corpus analysis and manual checking. The retrieved topics can be grouped into five general categories: multilingual-related, language teaching, and learning related, psycho/pathological/cognitive linguistics-related, methods and tools-related, and others. Topics such as bi/multilingual(ism), translanguaging, language/writing development, models, emotions, foreign language enjoyment (FLE), cognition, anxiety are among the most frequently explored. Multilingual and positive trends are discerned from the investigated HCPs. The findings inform linguistic researchers of the publication characteristics of the HCPs in the linguistics field and help them pinpoint the research trends and directions to exert their efforts in future studies.

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Section: Discussionmentioning

confidence: 99%

Trends and hot topics in linguistics studies from 2011 to 2021: A bibliometric analysis of highly cited papers

Song

Zhang²

2023

Front. Psychol.

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“…Since the present study focuses motivation research in the field of SLA, research articles published in high-quality journals in this field were included. Only published research articles were included for the reason that the quality and reliability of the unpublished preprints cannot be guaranteed due to a lack of a strict quality control mechanism such as peer review ( Zhu and Lei, 2022 ). As for the selection of the high-quality journals, many research used the list of 15 journals provided by VanPatten and Williams (2002) to investigate issues in SLA.…”

Section: Methodsmentioning

confidence: 99%

Motivation in second language acquisition: A bibliometric analysis between 2000 and 2021

2022

Front. Psychol.

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As one of the most important constructs of individual differences in second language learning, motivation has garnered a lot of attention in the area of Second Language Acquisition (SLA). Nevertheless, little bibliometric research has been conducted to provide a systematic overview of this line of research, which will help researchers to better understand how motivation-related research in SLA has evolved over the past 22 years and where it might push the boundaries of SLA research into in the future. In this study, three types of bibliometric analyses (i.e., co-citation analysis, citation analysis, and keyword analysis) were performed to identify the prominent scholarly documents, authors, venues of publications, and research topics that have been highly influential in the research of motivation in SLA between 2000 and 2021. Results from scientific network maps and keyword analysis suggest significant changes in the topic over the past 22 years. The results in this study also indicate an evident continuity of theoretic development in L2 language learning motivation research. Moreover, an air of active use of qualitative approaches has been detected in L2 language learning motivation research in the last 22 years.

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“…Last, trend analyses were performed to examine the time series data, namely, the MDD values at the sentential level and that of different dependency types from 1790 to 2017. Since the MDD values were not normally distributed (e.g., p = 0.000 for MDDs in sentences with 5-10 words), we followed Zhu and Lei (2022) and employed the Mann-Kendall trend test, a commonly used nonparametric test, to detect significant trends in time series, and Theil-Sen's slope estimator to calculate the corresponding rate of change. Both tests were implemented with the Python package pyMannKendall (Hussain and Mahmud, 2019; https://github.…”

Section: Methodsmentioning

confidence: 99%

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

Liu

Zhu

Lei

2022

Humanit Soc Sci Commun

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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.

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A dependency-based machine learning approach to the identification of research topics: a case in COVID-19 studies

Cited by 17 publications

References 41 publications

Trends and hot topics in linguistics studies from 2011 to 2021: A bibliometric analysis of highly cited papers

Trends and hot topics in linguistics studies from 2011 to 2021: A bibliometric analysis of highly cited papers

Motivation in second language acquisition: A bibliometric analysis between 2000 and 2021

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

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