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The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

A method for analyzing text using VOSviewer

Open access
Bukar, Umar Ali, Sayeed, Md Shohel, Razak, Siti Fatimah Abdul, Yogarayan, Sumendra, Amodu, Oluwatosin Ahmed, Mahmood, Raja Azlina Raja·2023·MethodsX

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.

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Metadata

Authors
Bukar, U. A., Sayeed, M. S., Razak, S. F. A., Yogarayan, S., Amodu, O. A., & Mahmood, R. A. R.
Venue
MethodsX
Publisher
Elsevier BV
Published
2023-12
Volume
11
Pages
102339
ISSN
2215-0161 (ISSN-L)
OpenAlex
W4386067316
Cited by
459
References
16
FWCI
221.72
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: A method for analyzing text using VOSviewer. https://app.cochat.ai/papers/10.1016/j.mex.2023.102339
The paper
Bukar, U. A., Sayeed, M. S., Razak, S. F. A., Yogarayan, S., Amodu, O. A., & Mahmood, R. A. R. (2023). A method for analyzing text using VOSviewer. MethodsX. https://doi.org/10.1016/j.mex.2023.102339

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.