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IJIET 2023 Vol.13(4): 614-620
doi: 10.18178/ijiet.2023.13.4.1845

Identifying Content-Related and Non-content-related Queries in Online Discussion Forums Using Voyant Tools

Neha* and Eunyoung Kim

Manuscript received January 4, 2022; revised March 4, 2022; accepted March 20, 2022.

Abstract—The overarching goal of this study was to assess the suitability of Voyant Tools to identify the frequency of content-related and non-content-related query subjects (thread title) and prioritize them based on their occurrence and importance in the online discussion forum. The dataset consisted of 296 query subjects collected from the discussion forums of practical and theoretical massive open online courses (MOOCs). The cirrus, correlation, and scatter plot features of Voyant Tools (a web-based application) were used to analyze the dataset. The Cirrus feature assisted with word frequency, and the Correlation feature helped with their co-occurrence in the online discussion forum. The Scatter plot feature was the most appropriate tool among the three tools implemented in the current study for generating the clusters of content-related and non-content-related query subjects. Overall, Voyant Tools was an effective resource capable of analyzing quantitative and qualitative data and providing visual output in various forms.

Index Terms—Massive open online courses (MOOC) discussion forum, query analysis, Voyant tools

The authors are with the School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan.
*Correspondence: neha11@jaist.ac.jp (N.)

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Cite: Neha* and Eunyoung Kim, "Identifying Content-Related and Non-content-related Queries in Online Discussion Forums Using Voyant Tools," International Journal of Information and Education Technology vol. 13, no. 4, pp. 614-620, 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Managing Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net

 

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