Keyness analysis at part of speech level
| dc.contributor.author | Boukernine, Hadjer | |
| dc.contributor.author | Bouri, Hadj | |
| dc.date.accessioned | 2021-11-08T04:59:50Z | |
| dc.date.available | 2021-11-08T04:59:50Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Recently, academic writing in especial has got a lot of scholarly interest. Even though there is a flourishing field of investigation focused on academic writing, no studies have utilized a keyness method to analyze learners' grammatical categories usage. Along with these studies and because of the lack of employing keyness analysis, the current corpus-based study aimed from one side to examine samples of 52 civilization master thesis abstracts from 2014 to 2019. From the other side, it attempted to identify the significant differences in the use of grammatical categories among females and males in comparison to the Brown and LOB corpus. The linguistic characteristics that need special attention are highlighted through keyness analysis at the part-of-speech level. It displays the grammatical categories that unusually appear frequently or infrequently in the writings of English learners (Lin, 2015). Significant statistical method including LogLikelihood (LL) was used to calculate statistics of keyword frequency lists in their tagged form for the research. The findings of the quantitative analysis of Corpus indicate, despite the variations in frequency noted between the genders, that most post-graduate students overuse all grammatical categories. The findings of this investigation show that field-specific academic keyword lists are necessary for English foreign language students who want to improve their academic writing skills. This type of research helps students to be aware of the various part of speech (POS) categorizations, particularly those that correspond to academic writing | ar |
| dc.identifier.uri | http://hdl.handle.net/123456789/11651 | |
| dc.language.iso | en | ar |
| dc.publisher | Université Oum El Bouaghi | ar |
| dc.subject | Part of speech | ar |
| dc.subject | Log-likelihood* | ar |
| dc.title | Keyness analysis at part of speech level | ar |
| dc.title.alternative | the case of civilization master theses abstracts at the University of Oum El Bouaghi | ar |
| dc.type | Other | ar |
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