A comprehensive bibliometric analysis of Apache Hadoop from 2008 to 2020

Abstract

Purpose

The purpose of this paper is to make an overview of 6,618 publications of Apache Hadoop from 2008 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field, as well as a preliminary knowledge of Apache Hadoop for interested researchers.

Design/methodology/approach

This paper employs the bibliometric analysis and visual analysis approaches to systematically study and analyze publications about Apache Hadoop in the Web of Science database. This study aims to investigate the topic of Apache Hadoop by means of bibliometric analysis with the aid of visualization applications. Through the bibliometric analysis of the collected documents, this paper analyzes the main statistical characteristics and cooperation networks. Research themes, research hotspots and future development trends are also investigated through the keyword analysis.

Findings

The research on Apache Hadoop is still the top priority in the future, and how to improve the performance of Apache Hadoop in the era of big data is one of the research hotspots.

Research limitations/implications

This paper makes a comprehensive analysis of Apache Hadoop with methods of bibliometrics, and it is valuable for researchers can quickly grasp the hot topics in this area.

Originality/value

This paper draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years, aiming to understand the development status and trends in this field and inspire new ideas for researchers.

Citation

Zhang, J. and Lin, M. (2023), "A comprehensive bibliometric analysis of Apache Hadoop from 2008 to 2020", International Journal of Intelligent Computing and Cybernetics, Vol. 16 No. 1, pp. 99-120. https://doi.org/10.1108/IJICC-01-2022-0004