A hypergraph model for representing scientific output
Representation and analysis of publication data in the form of a network has become a common method of illustrating and evaluating the scientific output of a group or of a scientific field. Co-authorship networks also reveal patterns and collaboration practices. In this paper we propose the use of a...
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| Veröffentlicht in: | Scientometrics 2018-12, Vol.117 (3), p.1361-1379 |
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| container_title | Scientometrics |
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| creator | Lung, Rodica Ioana Gaskó, Noémi Suciu, Mihai Alexandru |
| description | Representation and analysis of publication data in the form of a network has become a common method of illustrating and evaluating the scientific output of a group or of a scientific field. Co-authorship networks also reveal patterns and collaboration practices. In this paper we propose the use of a hypergraph model—a generalized network—to represent publication data by considering papers as hypergraph nodes. Hyperedges, connecting the nodes, represent the authors connecting all their papers. We show that this representation is more straightforward than other authorship network models. Using the hypergraph model we propose a collaboration measure of an author that reflects the influence of that author over the collaborations of its co-authors. We illustrate the introduced concepts by analyzing publishing data of computer scientists and mathematicians in Romania over a 10 year period. |
| doi_str_mv | 10.1007/s11192-018-2908-2 |
| format | Article |
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| ispartof | Scientometrics, 2018-12, Vol.117 (3), p.1361-1379 |
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| language | eng |
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| source | SpringerLink Journals - AutoHoldings |
| subjects | Academic publications Authoring Co authorship Collaboration Computer Science Data analysis Data processing Graph theory Graphs Information Storage and Retrieval Library Science Mathematical models Nodes Publication output Representations |
| title | A hypergraph model for representing scientific output |
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