Development of collaboration matrix using co-occurrence and combinatoric system as scientometrics analysis

Purpose - The purpose of this study is to propose a new method for revealing the collaboration frequencies among the author's name and the author's affiliation through various analysis and visualization methods. Design/methodology/approach - This study takes metadata of the author's n...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Collnet journal of scientometrics and information management Jg. 13; H. 2; S. 247 - 267
Hauptverfasser: Riyanto, Slamet, Subagyo, Hendro, Marlina, Ekawati, Yaniasih, Yaniasih, Rodiah, Rodiah
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New Delhi Routledge 03.07.2019
Taru Publications
Schlagworte:
Co-author network
Co-author pattern
Co-occurrence
Collaboration
Collaboration matrix
Combinatoric system
Comorbidity
Keywords
Machine learning
Membership
Scientometrics
Visualization
Writers
ISSN:0973-7766, 2168-930X
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Purpose - The purpose of this study is to propose a new method for revealing the collaboration frequencies among the author's name and the author's affiliation through various analysis and visualization methods. Design/methodology/approach - This study takes metadata of the author's name, author's affiliate, and keyword from National Scientific Repository (RIN). Each article will be extracted accord to the entity, the author's name is separated into first author, second author, third author, etc. The affiliation is also separated according to the author's affiliation using machine learning algorithms. Findings - The implementation of the collaboration matrix form of visualization can be used effectively in looking at the number of collaborative frequencies of scientific works among author's names and author's affiliations. Presentations and calculations of keywords that often appear in each scientific paper resulting from collaboration between name pairs can be used to identify the contents of the study of scientific articles as a whole, see the topics discussed and find out the trends and interests of research. Originality/value - This study applied collaboration matrix using cooccurrence and combinatoric methods. The result of the analysis is the number of collaboration among the authors and the highest number of collaborations will be placed on the top rank.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0973-7766
2168-930X
DOI:10.1080/09737766.2020.1723450