Visualizing the Intellectual Structure of the Fuzzy Linguistic Knowledge Domain: A Bibliometric Analysis
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Visualizing the Intellectual Structure of the Fuzzy Linguistic Knowledge Domain: A Bibliometric Analysis Dejian Yu1
•
Zeshui Xu2 • L. Martı´nez3
Received: 9 October 2019 / Revised: 6 July 2020 / Accepted: 2 September 2020 Taiwan Fuzzy Systems Association 2020
Abstract Ever since the 1970s when the idea of fuzzy linguistic variable was introduced by L. Zadeh, it has been heatedly discussed and widely used in engineering, information science, and many other research fields. With the rapid development and use, thousands of papers have been published on fuzzy linguistic, detailing both theoretical development and application-oriented studies, being a very important area in the Computational Intelligence field. Considering this massive document material over the past decades, the main purpose of this study is to explore the knowledge structure and citation landscape in this field based on scientometrics and bibliometrics. The document data used in this study are obtained through a topic search from Web of Science, including 4350 original research and review articles. The intellectual structure of fuzzy linguistic knowledge domain is analyzed, such as countries and territories, research institutions, and authors. The bibliographic landscape is analyzed, identifying research themes and current research hotspots through document co-
& Zeshui Xu [email protected] Dejian Yu [email protected] L. Martı´nez [email protected] 1
Business School, Nanjing Audit University, Nanjing 211815, Jiangsu, China
2
Business School, Sichuan University, Chengdu 610064, China
3
Department of Computer Science, University of Jae´n, Jae´n, Spain
citation analysis and citation burst detection methods. The research results of this article remarkably benefit to our understanding of the fuzzy linguistic knowledge domain. Keywords Bibliometrics Fuzzy linguistic Computing with words Linguistic variable CiteSpace
1 Introduction Since L. Zadeh introduced the language forms to describe the concept of linguistic variable in 1975 [75–77], the fuzzy linguistic theory and its applications have attracted great attention from scholars [24, 28, 39, 64]. It starts from the ambiguity and uncertainty of human thinking, and uses language information to describe the subjective preferences of decision-makers, which is conducive to improving the quality of decision-making. The results of fuzzy linguistic variable and knowledge have been widely used in a broad variety of fields such as information sciences [30, 46, 53], engineering [3, 23, 66], business and economics [22, 40, 82], and created enormous benefits to our economy and society. After more than 40 years of development, an increasing number of scholars have come to realize the importance of tracing the trajectory of fuzzy linguistic related researches. However, few studies have focused on the quantitative examination of the development path of fuzzy linguistic related researches. Most existing literature surveys are qualitative and subjective which may lead to unreliable evaluation results to
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