<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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&amp;L density peak clustering algorithm is the best. Using the R&amp;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&amp;L density peak clustering reaches 30.06%, and the effect of identifying verb pattern variation is the best.</p>
</abstract>

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.

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

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

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...

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

Online veröffentlicht: 30. Nov. 2022

Seitenbereich: 107 - 118

Eingereicht: 19. Mai 2022

Akzeptiert: 16. Aug. 2022

DOI: https://doi.org/10.2478/amns.2021.2.00277

Schlüsselwörter
metadiscourse, clustering algorithm, WMD model, English academic papers

© 2023 Yinbo Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Online veröffentlicht: 30. Nov. 2022

Seitenbereich: 107 - 118

Eingereicht: 19. Mai 2022

Akzeptiert: 16. Aug. 2022

DOI: https://doi.org/10.2478/amns.2021.2.00277

Schlüsselwörtermetadiscourse, clustering algorithm, WMD model, English academic papers

© 2023 Yinbo Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
metadiscourse, clustering algorithm, WMD model, English academic papers