An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective
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School of Management, Guangdong University of Technology, Guangzhou 510520, China
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Institute of Big Data Strategic Research, Guangdong University of Technology, Guangzhou 510006, China
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Discipline of Business Analytics, The University of Sydney Business School, The University of Sydney, Camperdown, NSW 2006, Australia
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School of Business, Wuyi University, Nanping 354300, China
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Zhongshan Institute, University of Electronic Science and Technology of China, Guangzhou 528400, China
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Economics and Management College, Civil Aviation University of China, Tianjin 300300, China
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School of Management, Guangdong University of Technology, Guangzhou 510520, China
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Authors to whom correspondence should be addressed.
Sustainability 2018, 10(3), 667; https://doi.org/10.3390/su10030667
Received: 6 February 2018 / Revised: 26 February 2018 / Accepted: 26 February 2018 / Published: 1 March 2018
(This article belongs to the Special Issue Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness)
Big data has been extensively applied to many fields and wanted for sustainable development. However, increasingly growing publications and the dynamic nature of research fronts pose challenges to understand the current research situation and sustainable development directions of big data. In this paper, we visually conducted a bibliometric study of big data literatures from the Web of Science (WoS) between 2002 and 2016, involving 4927 effective journal articles in 1729 journals contributed by 16,404 authors from 4137 institutions. The bibliometric results reveal the current annual publications distribution, journals distribution and co-citation network, institutions distribution and collaboration network, authors distribution, collaboration network and co-citation network, and research hotspots. The results can help researchers worldwide to understand the panorama of current big data research, to find the potential research gaps, and to focus on the future sustainable development directions.
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Keywords:
big data; visualizing; intellectual structure; big data environment; co-citation network; collaboration network; sustainability
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MDPI and ACS Style
Hu, F.; Liu, W.; Tsai, S.-B.; Gao, J.; Bin, N.; Chen, Q. An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective. Sustainability 2018, 10, 667.
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