Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks

dc.contributor.authorDing, Ying
dc.date.accessioned2011-01-25T13:31:05Z
dc.date.available2011-01-25T13:31:05Z
dc.date.issued2011-01
dc.description.abstractScientific collaboration and endorsement are well-established research topics which utilize three kinds of methods: survey/questionnaire, bibliometrics, and complex network analysis. This paper combines topic modeling and path-finding algorithms to determine whether productive authors tend to collaborate with or cite researchers with the same or different interests, and whether highly cited authors tend to collaborate with or cite each other. Taking information retrieval as a test field, the results show that productive authors tend to directly coauthor with and closely cite colleagues sharing the same research interests; they do not generally collaborate directly with colleagues having different research topics, but instead directly or indirectly cite them; and highly cited authors do not generally coauthor with each other, but closely cite each other.
dc.identifier.urihttps://hdl.handle.net/2022/9968
dc.language.isoen_US
dc.publisherJournal of Informetrics
dc.rightsThis work may be protected by copyright unless otherwise stated.
dc.subjectpath-finding algorithm
dc.subjecttopic modeling
dc.subjectscientific endorsement
dc.subjectScientific collaboration
dc.titleScientific collaboration and endorsement: Network analysis of coauthorship and citation networks
dc.typeArticle

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