Collostructional Analysis on Future Will in Malaysian English Online News

This study aimed to find out the attracted and repelled verbs occur in the construction of future will of Covid-19 vaccine in Malaysia and how these verbs indicate the predictability of vaccination for locals. A specific context of Covid-19 vaccine in Malaysia from February to April in 721 Malaysian English online newspaper were used as the source of data in this study. A sequential explanatory design was used in this research which consisted of simple collexeme analysis to get a list of attracted and repelled verbs in future will and qualitative descriptive to explain how those verbs indicate the predictability of vaccination for Malaysian. This study revealed that aspectual verbs (e.g., start, begin, continue), engender verbs (e.g., benefit, enable, result), and verbs of desire (e.g., need, deliberate) are the top three of attracted verbs classification. Meanwhile, in repelled verbs classification, it is nominated by verbs with predicative complement (e.g., accept, buy, address), verbs of creation and transformation (e.g., raise, assist), and engender verbs as well as aspectual verbs. Those attracted verbs also indicate the predictability of Covid-19 vaccine in Malaysia was limited to the distribution and how the vaccination program was prepared. This study is also expected to give practical implications on the use of collostructional analysis for further research in grammatical structures and semantical aspects especially on the methodology and data analysis as well as being reference and guidance for any related fields in terms of future will usage.

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Publication Details

Journal
Journal of English Language Studies
Published
2024-09-02
DOI
https://doi.org/10.30870/jels.v9i2.24198
Primary Topic
Education, Sociology, Communication Studies
Type
article
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Collostructional Analysis on Future Will in Malaysian English Online News

Deborah Tirtania Chrisna Pake Seko
Journal of English Language Studies
Education, Sociology, Communication Studies
article

Collostructional Analysis on Future Will in Malaysian English Online News

Deborah Tirtania Chrisna Pake Seko
article en

Abstract

This study aimed to find out the attracted and repelled verbs occur in the construction of future will of Covid-19 vaccine in Malaysia and how these verbs indicate the predictability of vaccination for locals. A specific context of Covid-19 vaccine in Malaysia from February to April in 721 Malaysian English online newspaper were used as the source of data in this study. A sequential explanatory design was used in this research which consisted of simple collexeme analysis to get a list of attracted and repelled verbs in future will and qualitative descriptive to explain how those verbs indicate the predictability of vaccination for Malaysian. This study revealed that aspectual verbs (e.g., start, begin, continue), engender verbs (e.g., benefit, enable, result), and verbs of desire (e.g., need, deliberate) are the top three of attracted verbs classification. Meanwhile, in repelled verbs classification, it is nominated by verbs with predicative complement (e.g., accept, buy, address), verbs of creation and transformation (e.g., raise, assist), and engender verbs as well as aspectual verbs. Those attracted verbs also indicate the predictability of Covid-19 vaccine in Malaysia was limited to the distribution and how the vaccination program was prepared. This study is also expected to give practical implications on the use of collostructional analysis for further research in grammatical structures and semantical aspects especially on the methodology and data analysis as well as being reference and guidance for any related fields in terms of future will usage.

Journal of English Language StudiesVol. 9(2)
National University of Malaysia (MY)
Openalex Percentile: Top 73%
Education, Sociology, Communication Studies
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Collostructional Analysis on Future Will in Malaysian English Online News — Deborah Tirtania Chrisna Pake Seko · Journal of English Language Studies (2024) | TGRS Research Map | TGRS