Lung, R.I., Gaskó, N. & Suciu, M.A. (2018) Scientometrics [Info Economics, Q2]

Publicat: 24 Noiembrie 2020

Lung, R.I., Gaskó, N. & Suciu, M.A. (2018) A hypergraph model for representing scientific output. Scientometrics, 117(3), 1361-1379.

DOI: https://doi.org/10.1007/s11192-018-2908-2

✓ Publisher: Springer
✓ Web of Science Core Collection: Science Citation Index Expanded, Social Sciences Citation Index
✓ Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science
✓ Article Influence Score (AIS): 0.527 (2018) / Q2 in Information Science & Library Science

Abstract: 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 modela generalized networkto 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.

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