Bibliometrics involves the quantitative analysis of publication patterns, citation statistics and research trends, providing crucial insights into academic impact and emerging study areas. This comparative analysis explores the innovative and ever evolving horizon of bibliometric analysis in academia and research. In the era characterized by a rapid increase in academic publications, the imperative to employ data analytics tools for extracting knowledge and making informed strategic decisions has grown substantially. This paper highlights the growing importance of data analytics tools in bibliometric analysis amidst the surge in academic publications. By transitioning from traditional literature reviews to advanced tools like VOSviewer, Origin Lab, SPSS and machine learning, the study illustrates how these technologies enhance bibliometric studies. A case study on nutrient recovery from human urine, analysing 520 refined papers from Scopus and Web of Science, demonstrates the application of these tools in identifying research trends, geospatial distribution and collaboration networks. This methodology underscores the effectiveness of data analytics in addressing real-world research challenges and advancing the field of bibliometrics.
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Ghosh et al. (2024) studied this question.
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