Visualization method for decision-making: a case study in bibliometric analysis

dc.creatorRoozbeh Haghnazar Koochaksaraei
dc.creatorFrederico Gadelha Guimarães
dc.creatorBabak Hamidzadeh
dc.creatorSarfaraz Hashemkhani Zolfani
dc.date.accessioned2023-07-25T17:32:17Z
dc.date.accessioned2025-09-09T00:23:53Z
dc.date.available2023-07-25T17:32:17Z
dc.date.issued2021
dc.format.mimetypepdf
dc.identifier.doihttps://doi.org/10.3390/math9090940
dc.identifier.issn2227-7390
dc.identifier.urihttps://hdl.handle.net/1843/56960
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofMathematics
dc.rightsAcesso Aberto
dc.subjectVisualização da informação
dc.subjectDecision making
dc.subjectEngenharia elétrica
dc.subjectBibliometria
dc.subject.otherData visualization
dc.subject.otherVIKOR
dc.subject.otherMulti-criteria decision making
dc.subject.otherRelational analyzing
dc.subject.otherRelational analyzing
dc.subject.otherBibliographic networks
dc.subject.otherBibliometrics
dc.titleVisualization method for decision-making: a case study in bibliometric analysis
dc.typeArtigo de periódico
local.citation.epage946
local.citation.issue9
local.citation.spage940
local.citation.volume9
local.description.resumoData and information visualization have drawn an increasingly wide range of interest from several academic fields and industries. Concurrently, exploring a huge set of data to support feasible decisions needs an organized method of Multi-Criteria Decision Making (MCDM). The dramatic increasing of data producing during the past decade makes visualization necessary as a presentation layer on the top of MCDM process. This study aims to propose an integrated strategy to rank the alternatives in the dataset, by combining data, MCDM methods, and visualization layers. In fact, the well designed combination of Information Visualization and MCDM provides a more user-friendly approach than the traditional methods. We investigate a case study in bibliometric analyses, which have become an important dimension and tool for evaluating the impact and performance of researchers, departments, and universities. Hence, finding the best and most reliable papers, authors, and publishers considering diverse criteria is one of the important challenges in science world. Therefore, this text is presenting a new strategy on the bibliometric dataset as a case study and it demonstrates that this strategy can be more meaningful for the end users than the current tools. Finally, the presented simulations illustrate the performance and utilization of this combination. In other words, the researchers of this study could design and implement a tool that overcomes the biggest challenges of data analyzing and ranking via a combination of MCDM and visualization methodologies that can provide a tremendous amount of insight and information from a massive dataset in an efficient way.
local.identifier.orcidhttps://orcid.org/0000-0003-4656-9887
local.identifier.orcidhttps://orcid.org/0000-0001-9238-8839
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICA
local.publisher.departmentENGENHARIA - ESCOLA DE ENGENHARIA
local.publisher.initialsUFMG
local.url.externahttps://www.mdpi.com/2227-7390/9/9/940

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