Bibliometric analysis on Pythagorean fuzzy sets during 2013-2020

Purpose The purpose of this paper is to make a comprehensive analysis of 354 publications about Pythagorean fuzzy sets (PFSs) from 2013 to 2020 in order to comprehensively understand their historical progress and current situation, as well as future development trend. Design/methodology/approach First, this paper describes the fundamental information of these publications on PFSs, including their data information, annual trend and prediction and basic features. Second, the most productive and influential authors, countries/regions, institutions and the most cited documents are presented in the form of evaluation indicators. Third, with the help of VOSviewer software, the visualization analysis is conducted to show the development status of PFSs publications at the level of authors, countries/regions, institutions and keywords. Finally, the burst detection of keywords, timezone review and timeline review are exported from CiteSpace software to analyze the hotspots and development trend on PFSs. Findings The annual PFSs publications present a quickly increasing trend. The most productive author is Wei Guiwu (China). Wei Guiwu and Wei Cun have the strongest cooperative relationship. Research limitations/implications The implication of this study is to provide a comprehensive perspective for the scholars who take a fancy to PFSs, and it is valuable for scholars to grasp the hotspots in this field in time. Originality/value It is the first paper that uses the bibliometric analysis to comprehensively analyze the publications on PFSs. It can help the scholars in the field of PFSs to quickly understand the development status and trend of PFSs.

Automated summary

This study comprehensively analyzed 354 publications on Pythagorean fuzzy sets (PFSs) from 2013 to 2020, revealing a quickly increasing trend in annual publications. The most productive author in this field is Wei Guiwu (China), with the strongest cooperative relationship identified between Wei Guiwu and Wei Cun.