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Article type: Research Article
Authors: Chen, Jin | Meng, Sun; * | Zhou, Wei
Affiliations: Business School, Yunnan University of Finance and Economics, Kunming, PR China
Correspondence: [*] Corresponding author. Sun Meng, Business School, Yunnan University of Finance and Economics, Kunming 650221, PR China. E-mail: mengsun_2004@163.com.
Abstract: In today’s society, many decision-making problems cannot be merely solved based on quantitative data. Even though some issues are able to be addressed by quantitative data, researchers may face the difficulty of obtaining accurate and sufficient numbers. Some qualitative evaluations given by experts or decision makers are usually linguistic expressions. Therefore, fuzzy linguistic research has been broadly studied to address the above issues. This research has also been attracting increasing attention from researchers and decision makers in the world. It is believed that analyzing the status quo and emerging trends in this research area is of great necessity, especially for the beginners who are interested in fuzzy linguistic research. To do so, this paper provides the mapping knowledge domain of fuzzy linguistic research based on 648 papers on Web of Science from 1975 to 2018 by using CiteSpace which is an effective tool for scientometric studies. The visualization analyses of cited reference clusters, collaborations networks, author co-citation networks, burst detection and time zone view are presented in this study to show the research streams and the papers that made significant theoretical contributions. Also, the active counties, institutions, journals and authors in this research area are analyzed in detail. Besides, the specific hot spots and emerging trends can be known. There are two contributions in this study. Firstly, we give a comprehensive investigation about the status quo and emerging trends of fuzzy linguistic research in the recent 43 years. Secondly, we make the development of fuzzy linguistic research easier and direct to learn for beginners.
Keywords: Fuzzy logic, linguistics, decision making, CiteSpace, scientometric
DOI: 10.3233/JIFS-182737
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3655-3669, 2019
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