Learner Corpus Research: A Bibliometric Analysis

Norwati Roslim, Muhammad Hakimi Tew Abdullah, Nur Faathinah Mohammad Roshdan, Yu Jin Ng, Seyed Ali Resvani Kalajahi

Abstract


This study aims to create a meaningful single-source reference for language and linguistic scholars concerning learner corpus research. The objectives of this study were firstly, to evaluate the trend of research on learner corpus; secondly, to determine key areas in learner corpus research, and thirdly, to identify the major players in learner corpus research. This study employed a bibliometric method to describe and analyse data on 902 works related to learner corpus. The data was retrieved in January 2023 from a Scopus database. VOSviewer software was used to visualize the data respectively. Findings showed that research on learner corpus started as early as 1994. The number of publications started to evolve in the year 2008 and the number of publications in 2022 appeared as the largest since 1994. The characteristics of scientific collaborations on learner corpus research reflect that there is still a scarcity of studies in this field based on papers published in the Scopus database. Thus, this bibliometric study can contribute as a reference for future research in complementing meta-analysis and structured literature reviews on learner corpus research.


Full Text:

PDF


DOI: https://doi.org/10.5296/ire.v11i2.21396

Refbacks

  • There are currently no refbacks.




Copyright (c) 2023 Norwati Roslim, Muhammad Hakimi Tew Abdullah, Nur Faathinah Mohammad Roshdan, Yu Jin Ng, Seyed Ali Resvani Kalajahi

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

 Contact: ire@macrothink.org

To make sure that you can receive messages from us, please add the 'macrothink.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.

Copyright © Macrothink Institute   ISSN 2327-5499