Research article | Open Access
Base for Electronic Educational Sciences 2025, Vol. 6(1) 91-103
Bibliometric Analysis Augmented by Artificial Intelligence: Implementation of pyBibX and a Practical Guide
pp. 91 - 103
Publish Date: March 30, 2025 | Single/Total View: 0/0 | Single/Total Download: 0/0
Abstract
In addition to providing performance-based information on variables such as author, journal, and country, bibliometric analysis studies can provide in-depth insights into trends in the field by creating scientific maps through text mining based on keywords, titles, and abstracts. Various software such as Vosviewer, Bibliometrix, SciMAT, BipExcel, and CiteSpace are frequently used in such analyses. However, these programs fall short when it comes to manipulating data or merging publications from different databases. The aim of this article is to provide an overview of the pyBibX application and its main features, as well as to examine the studies published in the Journal of National Education in terms of various variables. This will be achieved by using the potential benefits and effects of artificial intelligence-supported bibliometric analysis on the Scopus database data of these studies as an example. With the analysis carried out for this purpose, it is shown how the distribution of academic productivity in the journal according to years, keywords, and thematic clusters can be done with the pyBibx application.With the analysis carried out for this purpose, it is shown how the distribution of academic productivity in the journal according to years, keywords, and thematic clusters can be done with the pyBibx application. The application revealed that the journal, particularly in the post-pandemic periods, prominently featured themes such as distance education and digital transformation.
Keywords: bibliometrics analysis, bibliometrics tools, pyBibx, artificial intelligence, Journal of National Education
APA 7th edition
Balikci, H.C. (2025). Bibliometric Analysis Augmented by Artificial Intelligence: Implementation of pyBibX and a Practical Guide. Base for Electronic Educational Sciences, 6(1), 91-103.
Harvard
Balikci, H. (2025). Bibliometric Analysis Augmented by Artificial Intelligence: Implementation of pyBibX and a Practical Guide. Base for Electronic Educational Sciences, 6(1), pp. 91-103.
Chicago 16th edition
Balikci, Hasan Celal (2025). "Bibliometric Analysis Augmented by Artificial Intelligence: Implementation of pyBibX and a Practical Guide". Base for Electronic Educational Sciences 6 (1):91-103.
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