Insight into the Disciplinary Structure of Nanoscience & Nanotechnology

作     者：Chunjuan Luan Alan L.Porter 

作者机构：Faculty of Administration and LawDalian University of Technology School of Public PolicyGeorgia Institute of Technology 

出 版 物：《Journal of Data and Information Science》 (数据与情报科学学报（英文版）)

年 卷 期：2017年第2卷第1期

页      面：70-88页

核心收录：

学科分类：0401[教育学-教育学] 04[教育学] 07[理学] 070205[理学-凝聚态物理] 08[工学] 080501[工学-材料物理与化学] 0805[工学-材料科学与工程（可授工学、理学学位）] 040102[教育学-课程与教学论] 0702[理学-物理学] 

基　　金：supported by the National Natural Science Foundation of China(NSFC)(Grant No.:71473028) the Project of Dalian University of Technology (DLUT) Educational Reform(Grant No.:ZD201509) 

主　　题：Nanoscience & nanotechnology (N&N) Disciplinary structure Social network analysis Cluster analysis Cliques analysis Dynamic evolution 

摘      要：Purpose： This paper aims to gain an insight into the disciplinary structure of nanoscience ＆ nanotechnology （N＆N）： What is the disciplinary network of N＆N like？ Which disciplines are being integrated into N＆N over time？ For a specific discipline, how many other disciplines have direct or indirect connections with it？ What are the distinct subgroups of N＆N at different evolutionary stages？ Such critical issues are to be addressed in this paper. Design/methodology/approach： We map the disciplinary network structure of N＆N by employing the social network analysis tool, Netdraw, identifying which Web of Science Categories （WCs） mediate nbetweenness centrality in different stages of nano development. Cliques analysis embedded in the Ucinet program is applied to do the disciplinary cluster analysis in the study according to the path of ＂Network-Subgroup-Cliques,＂ and a tree diagram is selected as the visualizing type. Findings： The disciplinary network structure reveals the relationships among different disciplines in the N＆N developing process clearly, and it is easy for us to identify which disciplines are connected with the core ＂N＆N＂ directly or indirectly. The tree diagram showing N＆N related disciplines provides an interesting perspective on nano research and development （R＆D） structure. Research limitations： The matrices used to draw the N＆N disciplinary network are the original ones, and normalized matrix could be tried in future similar studies. Practical implications： Results in this paper can help us better understand the disciplinary structure of N＆N, and the dynamic evolution of N＆N related disciplines over time. The findings could benefit R＆D decision making. It can support policy makers from government agencies engaging in science and technology （S＆T） management or S＆T strategy planners to formulate efficient decisions according to a perspective of converging sciences and technologies. Originality/value： The novelty of this study lies in mapping the discipl