A scientometric methodology based on co-word analysis in gas turbine maintenance

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dc.contributor.authorNekoonam, Ali
dc.contributor.authorNasab, Reza Fatehi
dc.contributor.authorJafari, Soheil
dc.contributor.authorNikolaidis, Theoklis
dc.contributor.authorAle Ebrahim, Nader Ale
dc.contributor.authorMiran Fashandi, Seyed Alireza
dc.date.accessioned2023-01-09T13:54:41Z
dc.date.available2023-01-09T13:54:41Z
dc.date.issued2023-01-31
dc.description.abstractEvaluation of scientific journals has a profound effect on the future of scientific research so that different institutes and countries can set appropriate goals and invest with less risk in various scientific fields. Accordingly, this article presents a new method based on a combination of co-word analysis and social network analysis to extract the hotspot topics. Using HistCite, NodeXL, and VOSviewer, then combining their results, the desired analysis is conducted for six time periods. Based on the bibliographic parameters in HistCite and by defining an index, the first five periods are selected such that both quantity and quality of articles in each period are maximum compared to other years, while the sixth time period contains the latest research. For each of the six periods, the co-word networks as created in VOSviewer are analyzed. Next, based on a combination of network centralities developed in NodeXL, the hotspot keywords are specified which are then validated and aggregated using the bibliographic parameters in HistCite. The results reveal five important time periods in gas turbine maintenance. The hotspot keywords obtained for the last period show that in recent years, some topics including gas turbine fault prognosis, neural network-based approaches, big data analysis, sensor fault diagnosis, blade availability, economic analysis and useful life estimation are prominent subjects in gas turbine maintenance.en_UK
dc.identifier.citationNekoonam A, Naseb RF, Jafari S, et al., (2023) A scientometric methodology based on co-word analysis in gas turbine maintenance. Tehnicki Vjesnik/Technical Gazette, Volume 30, Issue 1, January 2023, 361-372en_UK
dc.identifier.issn1330-3651
dc.identifier.urihttps://doi.org/10.17559/TV-20220118165828
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18912
dc.language.isoenen_UK
dc.publisherFaculty of Mechanical Engineering in Slavonski Brod. et al.en_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectco-word analysisen_UK
dc.subjectgas turbine maintenanceen_UK
dc.subjectHistCiteen_UK
dc.subjectNodeXLen_UK
dc.subjectsocial network analysisen_UK
dc.subjectVOSvieweren_UK
dc.titleA scientometric methodology based on co-word analysis in gas turbine maintenanceen_UK
dc.typeArticleen_UK
dcterms.dateAccepted2022-12-15

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