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 accessAbstract
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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Cites
Software survey: VOSviewer, a computer program for bibliometric mapping
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Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Visualizing Bibliometric Networks
van Eck, N. J., & Waltman, L. (2014) · Measuring Scholarly Impact · doi:10.1007/978-3-319-10377-8_13 · Cited by 3,342
A unified approach to mapping and clustering of bibliometric networks
Waltman, L., van Eck, N. J., & Noyons, E. C. M. (2010) · Journal of Informetrics · doi:10.1016/j.joi.2010.07.002 · Cited by 2,224
Software tools for conducting bibliometric analysis in science: An up-to-date review
Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020) · El Profesional de la Información · doi:10.3145/epi.2020.ene.03 · Cited by 1,675
A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS
van Eck, N. J., Waltman, L., Dekker, R., & van den Berg, J. (2010) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21421 · Cited by 888
Text mining and visualization using VOSviewer
van Eck, N. J., & Waltman, L. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1109.2058 · Cited by 729
Big data and dynamic capabilities: a bibliometric analysis and systematic literature review
Rialti, R., Marzi, G., Ciappei, C., & Busso, D. (2019) · Management Decision · doi:10.1108/md-07-2018-0821 · Cited by 319
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Analysis of Big Data technologies for use in agro-environmental science
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Cited by
Badgujar, C. M., Poulose, A., & Gan, H. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.109090 · Cited by 411
Green Entrepreneurship for Sustainability Business: A Bibliometric Analysis
Manoharan, A. A., Rangaswamy, G., Muthukkannu, G., Sabapathi, S., Anandharaman, K., & N., A. A. T. (2024) · Journal of Lifestyle and SDGs Review · doi:10.47172/2965-730x.sdgsreview.v5.n02.pe03204 · Cited by 5
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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- 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.