Abstract
A Bibliometric analysis was applied in this paper to quantitatively evaluate the social network analysis research from 1975 to 2017 based on 7311 bibliographic records collected from the Science Citation Index (SCI) database. Firstly, a comprehensive analysis was conducted to reveal the current landscapes such as scientific outputs, international collaboration, subject categories, and research performances by individuals, we then use innovative methods such as Burst Detection, Referenced Publication Years Spectroscopy and Keyword Semantic Clustering to provide a dynamic view of the evolution of social network analysis research hotpots and trends from various perspectives. Results shows that social network analysis research has developed rapidly in the past four decades and is in the growth period with a maturity of 50.00%, the total of 7311 articles cover 120 countries (regions) and the top five most productive countries are USA, England, China, Canada and Germany. Among the 1181 major journal related to social network analysis, University of Illinois, University of Sydney and Carnegie Mellon University ranked as the top three. In addition burst keywords such as Knowledge Management, Centrality, Modularity, Community, Link Prediction, Learning Analytics and Big Data demonstrate the trends of this field. The result provides a dynamic view of the evolution of Social Network Analysis research landscapes, hotspots and trends from various perspectives which may serve as a potential guide for future research.
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Zeng, L., Li, Z., Zhao, Z., Mao, M. (2018). Mapping the Landscapes, Hotspots and Trends of the Social Network Analysis Research from 1975 to 2017. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10942. Springer, Cham. https://doi.org/10.1007/978-3-319-93818-9_30
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