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Article: Understanding scientific collaboration: Homophily, transitivity, and preferential attachment

TitleUnderstanding scientific collaboration: Homophily, transitivity, and preferential attachment
Authors
Issue Date2018
Citation
Journal of the Association for Information Science and Technology, 2018, v. 69, n. 1, p. 72-86 How to Cite?
Abstract© 2017 ASIS & T Scientific collaboration is essential in solving problems and breeding innovation. Coauthor network analysis has been utilized to study scholars' collaborations for a long time, but these studies have not simultaneously taken different collaboration features into consideration. In this paper, we present a systematic approach to analyze the differences in possibilities that two authors will cooperate as seen from the effects of homophily, transitivity, and preferential attachment. Exponential random graph models (ERGMs) are applied in this research. We find that different types of publications one author has written play diverse roles in his/her collaborations. An author's tendency to form new collaborations with her/his coauthors' collaborators is strong, where the more coauthors one author had before, the more new collaborators he/she will attract. We demonstrate that considering the authors' attributes and homophily effects as well as the transitivity and preferential attachment effects of the coauthorship network in which they are embedded helps us gain a comprehensive understanding of scientific collaboration.
Persistent Identifierhttp://hdl.handle.net/10722/285958
ISSN
2023 Impact Factor: 2.8
2023 SCImago Journal Rankings: 1.060
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Chenwei-
dc.contributor.authorBu, Yi-
dc.contributor.authorDing, Ying-
dc.contributor.authorXu, Jian-
dc.date.accessioned2020-08-18T04:57:05Z-
dc.date.available2020-08-18T04:57:05Z-
dc.date.issued2018-
dc.identifier.citationJournal of the Association for Information Science and Technology, 2018, v. 69, n. 1, p. 72-86-
dc.identifier.issn2330-1635-
dc.identifier.urihttp://hdl.handle.net/10722/285958-
dc.description.abstract© 2017 ASIS & T Scientific collaboration is essential in solving problems and breeding innovation. Coauthor network analysis has been utilized to study scholars' collaborations for a long time, but these studies have not simultaneously taken different collaboration features into consideration. In this paper, we present a systematic approach to analyze the differences in possibilities that two authors will cooperate as seen from the effects of homophily, transitivity, and preferential attachment. Exponential random graph models (ERGMs) are applied in this research. We find that different types of publications one author has written play diverse roles in his/her collaborations. An author's tendency to form new collaborations with her/his coauthors' collaborators is strong, where the more coauthors one author had before, the more new collaborators he/she will attract. We demonstrate that considering the authors' attributes and homophily effects as well as the transitivity and preferential attachment effects of the coauthorship network in which they are embedded helps us gain a comprehensive understanding of scientific collaboration.-
dc.languageeng-
dc.relation.ispartofJournal of the Association for Information Science and Technology-
dc.titleUnderstanding scientific collaboration: Homophily, transitivity, and preferential attachment-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/asi.23916-
dc.identifier.scopuseid_2-s2.0-85030028037-
dc.identifier.volume69-
dc.identifier.issue1-
dc.identifier.spage72-
dc.identifier.epage86-
dc.identifier.eissn2330-1643-
dc.identifier.isiWOS:000418157900007-
dc.identifier.issnl2330-1635-

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