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Abstract The Journal of Big Data has been a leading international journal in Decision Sciences and Computer Sciences. The goal of this research is to look into the Journal of Big Data's bibliometric attributes through scientific activity based on journal article citation links. Using a bibliometric approach, this study examines all of the journal's publications since its inception. The goal is to provide a comprehensive overview of the major factors influencing the journal. This analysis covers key issues such as the journal's publication and citation structure, the most cited articles, and the journal's leading authors, institutions, and countries. The network analysis was performed to look into author keywords through Journal of Big Data publications. The software that was utilized to create this analysis of present patterns and potential future developments was Scopus, Rstudio, and Vosviewer. A bibliometric study was utilized to examine articles and review papers, and only works published in the Scopus database between 2014 and 2021 were considered. The information on each manuscript's bibliometric was acquired after the findings were clearly explained. The initial findings included 632 articles.
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Mishra et al. (2023) studied this question.
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