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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Collnet journal of scientometrics and information management Ročník 13; číslo 2; s. 247 - 267
Hlavní autoři: Riyanto, Slamet, Subagyo, Hendro, Marlina, Ekawati, Yaniasih, Yaniasih, Rodiah, Rodiah
Médium: Journal Article
Jazyk:angličtina
Vydáno: New Delhi Routledge 03.07.2019
Taru Publications
Témata:
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
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie: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