A method for analyzing text using VOSviewer

Citation

Bukar, Umar Ali and Sayeed, Md. Shohel and Abdul Razak, Siti Fatimah and Yogarayan, Sumendra and Amodu, Oluwatosin Ahmed and Raja Mahmood, Raja Azlina (2023) A method for analyzing text using VOSviewer. MethodsX, 11. p. 102339. ISSN 2215-0161

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Abstract

The need for technical support for data handling and visualization solutions has increased in tandem with the complexity of today's data and information, that is of multiple sources, huge in size and of different formats. This study focuses on handling and analyzing text-based data. Despite many available text analysis tools, there is a high demand among researchers for easy- to-use tools yet scalable and with incomparable visualization features. Of recent, there has been a significant focus on utilizing VOSviewer, an open-source software for bibliometric analysis. This software is able to analyze a significant amount of data and provide excellent network data mapping. However, there is a lack of existing work in evaluating this sophisticated tool for text analysis. Thus, this article explores the capability of VOSviewer and presents evidence-based implementation of this software for text analysis. Specifically, this study demonstrates the usage of VOSviewer to analyze text based on YouTube interviews related to ChatGPT. Hence, this study significantly contributes by processing textual data and producing visualization network maps that are different from bibliometric data. The study recognizes VOSviewer as a powerful tool for data visualization in mapping text data and illustrates the potential of this software for analyzing text networks in various fields. • The study illustrates how text analysis and visualization can be realized using VOSviewer, an open-source software mostly used for biblio- metric analysis. • The study presents the workflow indicating how the dataset can be prepared as input for VOSviewer for text analysis. • The study proves that VOSviewer is a powerful tool for data visualization and network mapping for any type of network data including transcripts from social media.

Item Type: Article
Uncontrolled Keywords: Dataset, Text analysis, Visualization, VOSviewer
Subjects: N Fine Arts > N Visual arts
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 05 Oct 2023 01:29
Last Modified: 05 Oct 2023 01:29
URII: http://shdl.mmu.edu.my/id/eprint/11706

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