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Conference Paper: Understanding scientific collaboration from the perspective of collaborators and their network structures

TitleUnderstanding scientific collaboration from the perspective of collaborators and their network structures
Authors
Issue Date15-Mar-2016
PublisheriSchools
Abstract

Scientific collaboration is one of the key factors to trigger innovations. Coauthorship networks have been taken as representations of scholars’ collaboration for a long time. This study investigates how the authors’ attributes and the coauthorship network structures simultaneously influence the scientific collaboration among them. Exponential random graph models (ERGMs) are adopted in this research. We find that an author has a propensity to coauthor with the other scholar if they have different levels of productivity. We also find that the effect of network’s transitivity strongly influence authors’ collaboration. We demonstrate that taking the effects from both authors’ attributes and the network structures into consideration helps gain a comprehensive understanding of scientific collaboration.


Persistent Identifierhttp://hdl.handle.net/10722/342079

 

DC FieldValueLanguage
dc.contributor.authorZhang, Chenwei-
dc.contributor.authorBu, Yi-
dc.contributor.authorDing, Ying-
dc.date.accessioned2024-03-26T05:39:34Z-
dc.date.available2024-03-26T05:39:34Z-
dc.date.issued2016-03-15-
dc.identifier.urihttp://hdl.handle.net/10722/342079-
dc.description.abstract<p>Scientific collaboration is one of the key factors to trigger innovations. Coauthorship networks have been taken as representations of scholars’ collaboration for a long time. This study investigates how the authors’ attributes and the coauthorship network structures simultaneously influence the scientific collaboration among them. Exponential random graph models (ERGMs) are adopted in this research. We find that an author has a propensity to coauthor with the other scholar if they have different levels of productivity. We also find that the effect of network’s transitivity strongly influence authors’ collaboration. We demonstrate that taking the effects from both authors’ attributes and the network structures into consideration helps gain a comprehensive understanding of scientific collaboration.</p>-
dc.languageeng-
dc.publisheriSchools-
dc.relation.ispartofiConference 2016 (20/03/2016-23/03/2016, , , Philadelphia, Pennsylvania)-
dc.titleUnderstanding scientific collaboration from the perspective of collaborators and their network structures-
dc.typeConference_Paper-
dc.identifier.doi10.9776/16470-

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