Using Text Mining Techniques to Identify Research Trends: A Case Study of Design Research

被引:34
作者
Nie, Binling [1 ]
Sun, Shouqian [1 ]
机构
[1] Zhejiang Univ, Coll Comp Sci, Inst Ind Design, Hangzhou 310027, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2017年 / 7卷 / 04期
基金
中国国家自然科学基金;
关键词
text mining; bibliometric analysis; trend analysis; design research; SOCIAL INTERACTIONS; PERSPECTIVES; PERCEPTIONS; FATIGUE; QUALITY;
D O I
10.3390/app7040401
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The research goal of this paper is to identify major academic branches and to detect research trends in design research using text mining techniques. In this paper, the information about scientific literature in design research isprocessed. A combination of clustering and bibliometric analysis led to shaping four academic branches and summarizing each academic branch. Then, research trends and the evolution for each academic branch are explored. We perform a two-dimensional text mining approach, including bibliometric and network analysis, in order to detect trends of major academic branches. Specifically, the bibliometric characterization aims to assess design research area outputs, while the network analysis intends to reveal research trends in each academic branch of design research and the evolution of core research themes.
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页数:21
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