Abstract
This paper was explore a scientometric analysis of the research work in the emerging field of “Big Data” in recent years. Research on “Big Data” in the past few years, and in a short time has gained tremendous momentum. It is now considered one of the most important emerging research areas in computational science and related disciplines. By using the related literature in the Science Citation Index (SCI) database from 2006 to 2016, a scientometric approach was used to quantitatively assessing current research hotspots and trends. It shows that “Big Data” is a new emerging field with rapid development, the total of 2076 articles covered 131 countries (regions) and Top 3 countries (regions) were USA (731, 38.86%), China (373, 19.83%), England (93, 4.94%). In addition, Top 10 keywords are found to have citation bursts: epidemiology, scalability, social media, genomics, visualization, sequencing data, integration, intelligence, association, behavior. The results provided a dynamic view of the evolution of “Big Data” research hotpots and trends from various perspectives which may serve as a potential guide for future research.
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Zeng, L., Li, Z., Wu, T., Yang, L. (2017). Mapping Knowledge Domain Research in Big Data: From 2006 to 2016. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_24
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DOI: https://doi.org/10.1007/978-3-319-61845-6_24
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