Group-based Yule model for bipartite author-paper networks

This paper presents a model for author-paper networks, which is based on the assumption that authors are organized into groups and that, for each research topic, the number of papers published by a group is based on a success-breeds-success model. Collaboration between groups is modeled as random in...

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Bibliographic Details
Published inPhysical review. E, Statistical, nonlinear, and soft matter physics Vol. 71; no. 2 Pt 2; p. 026108
Main Authors Goldstein, Michel L, Morris, Steven A, Yen, Gary G
Format Journal Article
LanguageEnglish
Published United States 01.02.2005
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Summary:This paper presents a model for author-paper networks, which is based on the assumption that authors are organized into groups and that, for each research topic, the number of papers published by a group is based on a success-breeds-success model. Collaboration between groups is modeled as random invitations from a group to an outside member. To analyze the model, a number of different metrics that can be obtained in author-paper networks were extracted. A simulation example shows that this model can effectively mimic the behavior of a real-world author-paper network, extracted from a collection of 900 journal papers in the field of complex networks.
ISSN:1539-3755
DOI:10.1103/PhysRevE.71.026108