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dc.contributor.author Ding, Ying
dc.date.accessioned 2011-01-25T13:31:05Z
dc.date.available 2011-01-25T13:31:05Z
dc.date.issued 2011-01
dc.identifier.uri http://hdl.handle.net/2022/9968
dc.description.abstract Scientific 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. en
dc.language.iso en_US en
dc.publisher Journal of Informetrics en
dc.subject path-finding algorithm en
dc.subject topic modeling en
dc.subject scientific endorsement en
dc.subject Scientific collaboration en
dc.title Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks en
dc.type Article en


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