Analysing the variation of metadiscourse verb patterns in English academic papers from within and between disciplines

English is a universal language and is widely used. In order to deepen the cognition of language, this paper proposes to analyse the variation of metadiscourse verb patterns in English academic papers from within and between disciplines. By comparing the metadiscourse chunks used in various discipli...

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Veröffentlicht in:Applied mathematics and nonlinear sciences Jg. 8; H. 2; S. 107 - 118
1. Verfasser: Li, Yinbo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Beirut Sciendo 01.07.2023
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Schlagworte:
Clustering
clustering algorithm
Discourse analysis
English academic papers
metadiscourse
WMD model
ISSN:2444-8656, 2444-8656
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Zusammenfassung:English is a universal language and is widely used. In order to deepen the cognition of language, this paper proposes to analyse the variation of metadiscourse verb patterns in English academic papers from within and between disciplines. By comparing the metadiscourse chunks used in various disciplines, it is concluded that there are obvious differences in the verb types of the subject papers. Analysing various identification algorithms of verb types, it is obtained that the combination of the word movement distance (WMD) model and the R&L density peak clustering algorithm is the best. Using the R&L density peak clustering, identification parameters are easy to determine, and when combined with the WMD model to calculate the similarity of words, it improve the accuracy of verb pattern clustering. By comparison, it is proved that the accuracy of the algorithm combining the WMD model and R&L density peak clustering reaches 30.06%, and the effect of identifying verb pattern variation is the best.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2444-8656
2444-8656
DOI:10.2478/amns.2021.2.00277