Bibliometric Analysis in Scientific Research Using R: A Review of Scopus and Web of Science Databases

Yıl 2023, , 31 - 46, 25.06.2024

Mehmet Yıldız , Türkan Karakuş Yılmaz

https://doi.org/10.26650/JODA.1462396

Öz

The number of academic studies is increasing with the widespread use of digital tools. This increase makes it difficult to identify research trends, tendencies, themes, and other important points in various fields. Bibliometric analysis allows for the mapping of a field by analysing several academic studies and extracting meaningful conclusions. Therefore, bibliometric studies that are well conducted can build firm foundations for advancing a field in novel and meaningful ways. Bibliometric analysis, which is one of the approaches frequently used by researchers in the process of obtaining meaningful information from big data, has gained popularity especially in recent years. In this study, the bibliometrix package in the R programming language, which is frequently used in bibliometric analyses, is introduced and various analyses applied in the study are shown. Within the scope of this research, studies involving the R bibliometrix package were examined as sample applications. While bibliometric studies usually include the Scopus or Web of Science (WOS) databases, this study includes data obtained from both databases. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) steps were followed in the study. Accordingly, it provides an overview of bibliometric analysis, focussing in particular on its different techniques and providing step-by-step instructions on the procedures to be performed to perform bibliometric analysis with confidence. In the study, bibliometric analyses of 957 bibliometric studies obtained from the Wos and Scopus databases were also conducted. Because of the analysis, descriptive statistics such as year, author, journal, frequently used words, citations, etc. were presented.

Anahtar Kelimeler

Bibliometric Analysis, Biblioshiny, Bibliometrix, R Studio, Science mapping

Kaynakça

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