1. Introduction

The volume and diversity of scientific literature are expanding every day. A basis for future development is recorded in detail by abundant archived scientific literature. Data mining tries to discover information hidden in scientific literature, which is not accessible by simple statistical techniques. Text mining techniques area significant subset of data mining that aims to extract knowledge from unstructured or semi-structured textual data and has widespread applications in analyzing and processing textual documents. Hence, combining textual mining techniques and bibliometric analysis can be exploited to help us discover more unseen patterns in research fields than simple bibliometric analysis.

Great design has been the crucial point to make more aesthetically pleasing and more practical products and provide more adaptable services. It was revealed by the Design Management Institute that many design-centric companies like Apple and Target outperformed the S&P 500 by 224% from 2003–2013. Therefore, building a systematic view of design research becomes increasingly essential. Until now, analyzing the design research area from the perspective of scientometrics is still a largely unexplored area. To the best of our knowledge, there has been only one paper applying a quantitative approach to investigating the evolution and future trends of design research by analyzing citations of papers in the journal Design Studies. Additionally, few existing studies presented a qualitative method to analyze the design research area. Yet, there has been no in-depth study on keeping track of the current advances in the design research area.

Consequently, we use textual mining techniques to identify major academic branches and detect research trends in design research. Our work is perhaps the first such attempt of this kind to present a detailed bibliometric analysis in research fields.

This paper is organized as follows. We first gave a brief introduction in Section 1. Then, we explain the materials and methods in Section 2. Next, experiment results show the identification of major academic branches and their trends in Section 3. Finally, we discuss the results and make some conclusions in Section 3 and Section 4.