Trend Analysis of Fluency-Related Research Articles: Using Data Mining

Authors

  • Shinjae Park

    General Education Department, Kookmin University, Seoul 02707, Korea

DOI:

https://doi.org/10.30564/fls.v6i4.6797
Received: 25 June 2024 | Revised: 18 July 2024 | Accepted: 23 July 2024 | Published Online: 15 October 2024

Abstract

This research seeks to identify recent research trends in analysing fluency in English language studies since 2010. The importance of studying corpora that compile registered research in linguistics is growing; thus, it is time to consider the significance of data mining analysis on the corpora. Considering this emerging research topic, this analysis intends to generate and compare word clouds and word metric charts from speaking and writing abstract corpora in linguistics research centred on the keyword ‘Fluency’. This comparison is minimally addressed in extant research; hence, this investigation aims to fill this gap. The corpus contains 50 speaking and 15 writing abstracts from linguistics journals. To create the word cloud, AntConc4.1.4 software was used to analyse the corpora, while TF-IDF and matrix analysis were conducted using R. As a result, in spoken English, ‘fluency’ studies were largely related to 'teaching' and tended to be dominated by studies focusing on ‘fluency’ alone. In contrast, writing studies were mostly related to learner proficiency and assessment, and many studies analysed the relationship between linguistic abilities by expanding the scope of ‘fluency’ to include ‘accuracy’ and ‘complexity’. This study will benefit researchers in deciding on topics as it provides research directions and trends in analysing fluency in the two interconnected but differently expressed fields (i.e., speaking and writing).

Keywords:

Word cloud; Text mining; Fluency; Speaking; Writing

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How to Cite

Park, S. (2024). Trend Analysis of Fluency-Related Research Articles: Using Data Mining. Forum for Linguistic Studies, 6(4), 449–462. https://doi.org/10.30564/fls.v6i4.6797

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