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A corpus-driven analysis of phrase frames in research articles on business management

Datos Bibliográficos

ID21757358
AutoresMengyu He (0000-0001-9229-3223, Hubei University of Economics), Leng Hong Ang (0000-0001-5688-7753, Universiti Sains Malaysia, autor de correspondencia), Kim Hua Tan (0000-0003-3787-5006, National University of Malaysia)
Año2021
Volumen39
Número2
Páginas139-151
Fecha de publicación2021-04-03
Open AccessNo
TipoARTICLE
RevistaSouthern African Linguistics and Applied Language Studies (JOURNAL)
Identificadores de la revistaISSN: 1607-3614 • E-ISSN: 1727-9461
EditorialNational Inquiry Services Center (NISC) (PUBLISHER)
DOI10.2989/16073614.2021.1920438
OpenAlexW3174678899
IdiomaEN
Citas recibidas3
Referencias citadas47

With emerging developments in the use of computer and corpus-linguistic software to analyse language features and linguistic patterns, competent language users frequently rely on a stock of semi-automatic, prefabricated word chunks, rather than constantly creating new combinations of individual words. This has illuminated ways to improve academic writing among novice writers and students. Researchers have begun compiling academic expressions by deriving pedagogically useful lists of phraseological expressions, such as collocations (e.g. dark night), lexical bundles (e.g. the importance of) and phrase frames (e.g. the * of). These studies have widely advocated the use of a wide-angle approach in compiling academic phraseological expressions by focusing on language forms common in all disciplines. In the current corpus-driven study, we expand this line of research by arguing that discipline-specific academic phraseological expressions should be explored further by focusing on phrase frames that have so far received little attention from scholars. Findings from the study will help novice writers and students by providing them a repository of phrase frames that are pedagogically useful

Corpus linguistics · Genre analysis · Linguistics · Natural language processing · Phrase · Programming language · Computer Science · Discourse Analysis in Language Studies · Language, Metaphor, and Cognition · Second Language Acquisition and Learning · Artificial Intelligence · Software

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Citas por año1,5
Intervalo de citas2024 - 2025 (2)
Altamente citadoNo

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