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

Institute of Industrial Design, College of Computer Science, Zhejiang University, Hangzhou 310027, China
Author to whom correspondence should be addressed.
Academic Editor: Yang Kuang
Appl. Sci. 2017, 7(4), 401;
Received: 23 December 2016 / Revised: 21 March 2017 / Accepted: 11 April 2017 / Published: 15 April 2017
PDF [6896 KB, uploaded 19 April 2017]


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. View Full-Text
Keywords: text mining; bibliometric analysis; trend analysis; design research text mining; bibliometric analysis; trend analysis; design research

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Nie, B.; Sun, S. Using Text Mining Techniques to Identify Research Trends: A Case Study of Design Research. Appl. Sci. 2017, 7, 401.

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