Trends and Pattern in Big Data: A Bibliometric Study

Authors

  • Radha Raghuramapatruni Associate Professor, GITAM School of Business, GITAM Deemed to be University, Visakhapatnam, Andhra Pradesh, India

Keywords:

Bibliometric analysis, Big data, Scopus, Thematic map, Citations, Co-occurrence of words

Abstract

Purpose –The goal of the present study is to provide bibliometric analysis in order to gain insight into the evolution of the literature in the field of big data science.

Methodology- This study leveraged bibliometric techniques to examine a dataset of 3255 articles published between 2015-2023 using Vosviewer software. The main focus of the study was the performance analysis and the scientific mapping of articles.

Findings- An overview of big data analysis and the patterns in publications over the last eight years were included in this study. It showed that "Big Data" were the most popular keywords, and that countries like the US, China, Thailand, Australia, and India have a lot of publications in this area. The highest number of publications on big data was in China followed by US, India, UK and South Korea. The analysis showed that computer science, Decision Science, and math are the main areas where more research has been done on big data and data science.

Practical implications – Researchers from a variety of fields, especially those studying big data, may find this study to be a useful tool for tracking the development of scientific publications over time in a particular area.

Originality/value – The purpose of this study is to do a detailed analysis of prior research in the field of big data, which has been ongoing for more than 8 years. This analysis should provide some insight into the key developments that have occurred in big data during that period of eight years. The techniques employed result in a more comprehensive and in-depth analysis.

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References

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Published

29.01.2024

How to Cite

Raghuramapatruni, R. . (2024). Trends and Pattern in Big Data: A Bibliometric Study. International Journal of Intelligent Systems and Applications in Engineering, 12(13s), 322–333. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4599

Issue

Vol. 12 No. 13s (2024)

Section

Research Article

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