Title: A bibliometric analysis on Data Mining and Big Data

Authors: Shu-Feng Tseng; Yu-Ling Won; Jiann-Min Yang

Addresses: Department of MIS, National Chengchi University, No. 64, Sec. 2, Zhinan Rd., Wenshan Dist., Taipei City 116, Taiwan ' Department of MIS, National Chengchi University, No. 64, Sec. 2, Zhinan Rd., Wenshan Dist., Taipei City 116, Taiwan ' Department of MIS, National Chengchi University, No. 64, Sec. 2, Zhinan Rd., Wenshan Dist., Taipei City 116, Taiwan

Abstract: Along with more and faster accumulation of electronic business data, Data Mining and the newer Big Data issues are attracting more attention. This paper reports the literature analysis based on the publication journals and articles in the research databases. The ranking comparisons of top 10 article counts in 2014 on Data Mining and Big Data show that there are 9 in common in the top 10 author countries but only 2 in common in the top 10 author organisations. There are 6 in common in the top 10 research areas but only 2 in common in the top 10 journal names. However, near 1/3 authors contributing to the Big Data literature come from the pool of authors who have publications in the Data Mining subject. Hopefully, their Big Data research in the value dimension may link better to the Data Mining knowledge and methodologies.

Keywords: data mining; bibliometric analysis; big data; Bradford's Law; Bradford-Zipf's Law; literature review.

DOI: 10.1504/IJEB.2016.075333

International Journal of Electronic Business, 2016 Vol.13 No.1, pp.38 - 69

Received: 14 May 2015
Accepted: 28 Jul 2015

Published online: 15 Mar 2016 *

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