• Asia Pacific Journal of Corpus Research
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• v.5 no.1
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• pp.1-21
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• 2024

This study aimed to identify target lexical bundles (e.g., on the other hand, at the same time) for argumentative essay writing and rank them in order of teaching priority for Japanese learners. Despite significant functional roles of lexical bundles in academic writing, the inclusion of lexical bundles in argumentative writing had been underexplored. Since argumentative writing skills help undergraduate students prepare for their academic careers (e.g., writing papers), the lexical bundles under this genre deserve more attention. This study first extracted 78 target bundles from L1 argumentative essay corpora (International Corpus Network of Asian Learners of English: ICNALE and Louvain Corpus of Native English Essays: LOCNESS). The study then classified the bundles according to their discourse functions and semantic transparency to estimate the learnability for Japanese learners in L2 compatible corpora with the ICNALE. The results showed that learners had difficulty using the bundles with referential functions (e.g., in the form of) and semantic opaqueness (e.g., when it comes to), suggesting that the bundles in these two categories should be prioritized among the 78 bundles.

• International Journal of Contents
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• v.14 no.4
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• pp.70-75
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• 2018

The purpose of this corpus-based study was to find 4-word lexical bundles in computer science research articles. As the demand for research articles (RAs) for international publication increases, the need for acquiring field-specific writing conventions for this academic genre has become a burning issue. Particularly, one area of burgeoning interest in the examination of rhetorical structures and linguistic features of RAs is the use of lexical bundles, the indispensable building blocks that make up an academic discourse. To illustrate, different academic discourses rely on distinctive repertoires of lexical bundles. Because lexical bundles are often acquired as a whole, the recurring multi-word sequences can be retrieved automatically to make written discourse more fluent and natural. Therefore, the proper use of rhetorical devices specific to a particular discipline can be a vital indicator of success within the discourse communities. Hence, to identify linguistic features that make up specific registers, this corpus-based study examines the types and usage frequency of lexical bundles in the discipline of CS, one of the most in-demand fields world over. Given that lexical bundles are empirically-derived formulaic multi-word units, identifying core lexical bundles used in RAs, they may provide insights into the specificity of particular CS text types. This will in turn provide empirical evidence of register specificity and technicality within the academic discourse of computer science. As in the results, pedagogical implications and suggestions for future research are discussed.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.426-435
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• 2021

This study aims to functionally classify lexical bundles appearing in academic papers on nuclear science and engineering written in English and then analyze the lexical bundles' characteristics compared to those appearing in general academic papers. To this end, the texts of nuclear science and engineering papers were collected and produced as a corpus(c. 1 mil. tokens). Then they were statistically compared through Chi-square tests and standardized residuals with the corpus of general academic papers(c. 750,000 tokens). The results revealed that, compared to general academic papers, the bundles in the stance lexical bundle category were mainly used among the functional lexical bundle in nuclear science and engineering. The use of the lexical bundles lacked much variety. The same type of lexical bundles was 're-used' and 'recycled'. Based on these research results, educational implications for English for Academic Purposes and the further direction of follow-up research were discussed and suggested.

• Asia Pacific Journal of Corpus Research
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• v.2 no.2
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• pp.17-29
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• 2021

The current study explores small corpora of critiques written by Chinese and non-Chinese university students and how strategies used by these writers compare with high-rated L1 students. Data collection includes three small corpora of student writing; 20 student critiques in 2017, 23 student critiques from 2018, and 23 critiques from the online Michigan MICUSP collection at the University of Michigan. The researchers employ Text Inspector and Lexical Complexity to identify university students' vocabulary knowledge and awareness of syntactic complexity. In addition, WMatrix4® is used to identify and support the comparison of lexical and semantic differences among the three corpora. The findings indicate that gaps between Chinese and non-Chinese writers in the same university classes exist in students' knowledge of grammatical features and interactional metadiscourse. In addition, critiques by Chinese writers are more likely to produce shorter clauses and sentences. In addition, the mean value of complex nominal and coordinate phrases is smaller for Chinese students than for non-Chinese and MICUSP writers. Finally, in terms of lexical bundles, Chinese student writers prefer clausal bundles instead of phrasal bundles, which, according to previous studies, are more often found in texts of skilled writers. The current study's findings suggest incorporating implicit and explicit instruction through the implementation of corpora in language classrooms to advance skills and strategies of all, but particularly of Chinese writers of English.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.333-342
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• 2021

In this study, we analyzed the vocabulary, lemmas, keywords, and n-grams in 『Treasure Island』 to identify certain linguistic features of this British-American children's adventure novel. The current study found that, contrary to the popular claim that frequently-used words are important and essential to a story, the set of frequently-used words in 『Treasure Island』 were mostly function words and proper nouns that were not directly related to the plot found in 『Treasure Island』. We also ascertained that a list of keywords using a statistical method making use of a corpus program was not good enough to surmise the story of 『Treasure Island』. However, we managed to extract 30 keywords through the first quantitative keyword analysis and then a second qualitative keyword analysis. We also carried out a series of n-gram analyses and were able to discover lexical bundles that were preferred and frequently used by the author of 『Treasure Island』. We hope that the results of this study will help spread this knowledge among British-American children's literature as well as to further put forward corpus stylistic theory.

• Cross-Cultural Studies
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• v.45
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• pp.109-143
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• 2016

This article examines distinctive linguistic shifts of translational English in an effort to verify the validity of the translation universals hypotheses, including simplification, explicitation, normalization and leveling-out, which have been most heavily explored to date. A large-scale study involving comparable corpora of translated and non-translated English newspaper texts has been carried out to typify particular linguistic attributes inherent in translated texts. The main findings are as follows. First, by employing the parameters of STTR, top-to-bottom frequency words, and mean values of sentence lengths, the translational instances of simplification have been detected across the translated English newspaper corpora. In contrast, the portion of function words produced contrary results, which in turn suggests that this feature might not constitute an effective test of the hypothesis. Second, it was found that the use of connectives was more salient in original English newspaper texts than translated English texts, being incompatible with the explicitation hypothesis. Third, as an indicator of translational normalization, lexical bundles were found to be more pervasive in translated texts than in non-translated texts, which is expected from and therefore support the normalization hypothesis. Finally, the standard deviations of both STTR and mean sentence lengths turned out to be higher in translated texts, indicating that the translated English newspaper texts were less leveled out within the same corpus group, which is opposed to what the leveling-out hypothesis postulates. Overall, the results suggest that not all four hypotheses may qualify for the label translation universals, or at least that some translational predictors are not feasible enough to evaluate the effectiveness of the translation universals hypotheses.