A decade of big data literature: Analysis of trends in light of bibliometrics
Document Type
Article
Publication Date
5-1-2020
Abstract
Bibliometrics is a quantitative tool for the analysis of literature published in a scientific field. Using Scopus as the data source, we perform a thorough analysis of scholarly works published in the field of big data from 2008 to 2017. The objective of the work is to find the most cited articles in the given time frame, the citation trends, the authorship trends as well as the trends of research work in the related area. The analysis shows that over 50% of publications do not receive any citations, and the average number of citations per publication is 3.17. It is also observed that single authorship of research publications has declined over the time. The analysis reveals the pioneering role played by the USA in advancing the research in big data, which has lately been taken over by China, and the large-scale usage of big data analytics in various domains of science.
Keywords
Big data, Bibliometric analysis, Citation analysis
Divisions
universiti
Funders
None
Publication Title
Journal of Supercomputing
Volume
76
Issue
5, SI
Publisher
Springer
Publisher Location
VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS