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Ranking scientific publications: the effect of nonlinearity
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 proc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4200399/ https://www.ncbi.nlm.nih.gov/pubmed/25322852 http://dx.doi.org/10.1038/srep06663 |
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author | Yao, Liyang Wei, Tian Zeng, An Fan, Ying Di, Zengru |
author_facet | Yao, Liyang Wei, Tian Zeng, An Fan, Ying Di, Zengru |
author_sort | Yao, Liyang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4200399 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-42003992014-10-21 Ranking scientific publications: the effect of nonlinearity Yao, Liyang Wei, Tian Zeng, An Fan, Ying Di, Zengru Sci Rep Article 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. Nature Publishing Group 2014-10-17 /pmc/articles/PMC4200399/ /pubmed/25322852 http://dx.doi.org/10.1038/srep06663 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ |
spellingShingle | Article Yao, Liyang Wei, Tian Zeng, An Fan, Ying Di, Zengru Ranking scientific publications: the effect of nonlinearity |
title | Ranking scientific publications: the effect of nonlinearity |
title_full | Ranking scientific publications: the effect of nonlinearity |
title_fullStr | Ranking scientific publications: the effect of nonlinearity |
title_full_unstemmed | Ranking scientific publications: the effect of nonlinearity |
title_short | Ranking scientific publications: the effect of nonlinearity |
title_sort | ranking scientific publications: the effect of nonlinearity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4200399/ https://www.ncbi.nlm.nih.gov/pubmed/25322852 http://dx.doi.org/10.1038/srep06663 |
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