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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Published in | Physical review. E, Statistical, nonlinear, and soft matter physics Vol. 71; no. 2 Pt 2; p. 026108 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
01.02.2005
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Online Access | Get more information |
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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. |
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ISSN: | 1539-3755 |
DOI: | 10.1103/PhysRevE.71.026108 |