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Scientometric mapping of research on ‘Big Data’

Author

Listed:
  • Vivek Kumar Singh

    (South Asian University)

  • Sumit Kumar Banshal

    (South Asian University)

  • Khushboo Singhal

    (South Asian University)

  • Ashraf Uddin

    (South Asian University)

Abstract

This paper presents a scientometric analysis of research work done on the emerging area of ‘Big Data’ during the recent years. Research on ‘Big Data’ started during last few years and within a short span of time has gained tremendous momentum. It is now considered one of the most important emerging areas of research in computational sciences and related disciplines. We have analyzed the research output data on ‘Big Data’ during 2010–2014 indexed in both, the Web of Knowledge and Scopus. The analysis maps comprehensively the parameters of total output, growth of output, authorship and country-level collaboration patterns, major contributors (countries, institutions and individuals), top publication sources, thematic trends and emerging themes in the field. The paper presents an elaborate and one of its kind scientometric mapping of research on ‘Big Data’.

Suggested Citation

  • Vivek Kumar Singh & Sumit Kumar Banshal & Khushboo Singhal & Ashraf Uddin, 2015. "Scientometric mapping of research on ‘Big Data’," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 727-741, November.
    • Handle: RePEc:spr:scient:v:105:y:2015:i:2:d:10.1007_s11192-015-1729-9
    DOI: 10.1007/s11192-015-1729-9
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    Cited by:

    1. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    2. Daphne R. Raban & Avishag Gordon, 2020. "The evolution of data science and big data research: A bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1563-1581, March.
    3. Xiaozan Lyu & Rodrigo Costas, 2021. "Studying the characteristics of scientific communities using individual-level bibliometrics: the case of Big Data research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6965-6987, August.

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