Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study
作者： Yi Zhang , Ying Huang , Alan L. Porter , Guangquan Zhang , Jie Lu
DOI: 10.1016/J.TECHFORE.2018.06.007
关键词:
摘要: Abstract As one of the most impactful emerging technologies, big data analytics and its related applications are powering development information technologies significantly shaping thinking behavior in today's interconnected world. Exploring technological evolution research is an effective way to enhance technology management create value for strategies both government industry. This paper uses a learning-enhanced bibliometric study discover interactions by detecting visualizing evolutionary pathways. Concentrating on set 5840 articles derived from Web Science covering period between 2000 2015, text mining techniques combined profile hotspots core constituents. A learning process used ability identify interactive relationships topics sequential time slices, revealing death. The outputs include landscape within 2015 with detailed map pathways specific technologies. Empirical insights studies science policy, innovation management, entrepreneurship also provided.
sci-hub.se 参考文章(58)
Andrew McAfee, Erik Brynjolfsson, Thomas H Davenport, DJ Patil, Dominic Barton, None, Big data: the management revolution. Harvard Business Review. ,vol. 90, pp. 60- 128 ,(2012)
MG Moehrle, R Phaal, R Isenmann, Technology roadmapping for strategy and innovation : charting the route to success Springer Berlin. ,(2013)
Ying Huang, Jannik Schuehle, Alan L. Porter, Jan Youtie, A systematic method to create search strategies for emerging technologies based on the Web of Science: illustrated for `Big Data' Scientometrics. ,vol. 105, pp. 2005- 2022 ,(2015) , 10.1007/S11192-015-1638-Y
J. Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, Angela Hung Byers, Big data: The next frontier for innovation, competition, and productivity ,(2011)
Vivek Kumar Singh, Sumit Kumar Banshal, Khushboo Singhal, Ashraf Uddin, None, Scientometric mapping of research on `Big Data' Scientometrics. ,vol. 105, pp. 727- 741 ,(2015) , 10.1007/S11192-015-1729-9
Ronald Margolis, Leslie Derr, Michelle Dunn, Michael Huerta, Jennie Larkin, Jerry Sheehan, Mark Guyer, Eric D Green, The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data Journal of the American Medical Informatics Association. ,vol. 21, pp. 957- 958 ,(2014) , 10.1136/AMIAJNL-2014-002974
Gerard Salton, Michael J. McGill, Introduction to Modern Information Retrieval ,(1983)
Henry Small, Kevin W. Boyack, Richard Klavans, Identifying emerging topics in science and technology Research Policy. ,vol. 43, pp. 1450- 1467 ,(2014) , 10.1016/J.RESPOL.2014.02.005
Yuya Kajikawa, Junta Yoshikawa, Yoshiyuki Takeda, Katsumori Matsushima, Tracking emerging technologies in energy research : toward a roadmap for sustainable energy Technological Forecasting and Social Change. ,vol. 75, pp. 771- 782 ,(2008) , 10.1016/J.TECHFORE.2007.05.005
Gerard Salton, Christopher Buckley, Term Weighting Approaches in Automatic Text Retrieval Information Processing and Management. ,vol. 24, pp. 323- 328 ,(1988) , 10.1016/0306-4573(88)90021-0