Ranking scientific publications: the effect of nonlinearity
- Yao, Liyang School of Systems Science, Beijing Normal University, Beijing, China
- Wei, Tian School of Systems Science, Beijing Normal University, Beijing, China
- Zeng, An School of Systems Science, Beijing Normal University, Beijing, China - Department of Physics, University of Fribourg, Switzerland
- Fan, Ying School of Systems Science, Beijing Normal University, Beijing, China
- Di, Zengru School of Systems Science, Beijing Normal University, Beijing, China
-
17.10.2014
Published in:
- Scientific Reports. - 2014, vol. 4, no. 1, p. 6663
English
Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Physique
- Language
-
- English
- Classification
- Physics
- License
- License undefined
- Identifiers
-
- RERO DOC 233261
- DOI 10.1038/srep06663
- Persistent URL
- https://folia.unifr.ch/unifr/documents/304166
Statistics
Document views: 23
File downloads:
- zen_rsp.pdf: 23