Global Research Trends in “Big Data” during 2012-21: A Data Mining based on Scientometric Tools

Abstract

The term “big data” is becoming widespread throughout the world, as it has wide usage because it is no longer limited to the IT industry and entrepreneurship but has entered every aspect of media and communications. But the reason for using big data is only it’s ability in searching, collecting and interpreting huge datasets. Now, the purpose of this paper is to scrutinize the papers related to big data and other relevant fields. Using bibliometric methods and techniques these papers are analyzed and reviewed. The author examined the citation behavior, co-authorship patterns, research hot spots, and trending topics using both traditional and state-of-the-art network visualization and text mining in bibliometric techniques. From the analysis of keyword co-occurrence, a set of 12 clusters of keywords are discovered. Each cluster with identical color and theme. The research hot spots discovered are blockchain, digital twin, artificial intelligence, and the internet of things. The emergence of these keywords indicate that these areas are having lot of scope for future research. To best of knowledge, this study is a first attempt to discover the research streams and will help the researchers to work in these areas to explore new areas and applications of big data in relevant fields.