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Identification of milestone papers through time-balanced network centrality

Author

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  • Mariani, Manuel Sebastian
  • Medo, Matúš
  • Zhang, Yi-Cheng

Abstract

Citations between scientific papers and related bibliometric indices, such as the h-index for authors and the impact factor for journals, are being increasingly used – often in controversial ways – as quantitative tools for research evaluation. Yet, a fundamental research question remains still open: to which extent do quantitative metrics capture the significance of scientific works? We analyze the network of citations among the 449,935 papers published by the American Physical Society (APS) journals between 1893 and 2009, and focus on the comparison of metrics built on the citation count with network-based metrics. We contrast five article-level metrics with respect to the rankings that they assign to a set of fundamental papers, called Milestone Letters, carefully selected by the APS editors for “making long-lived contributions to physics, either by announcing significant discoveries, or by initiating new areas of research”. A new metric, which combines PageRank centrality with the explicit requirement that paper score is not biased by paper age, is the best-performing metric overall in identifying the Milestone Letters. The lack of time bias in the new metric makes it also possible to use it to compare papers of different age on the same scale. We find that network-based metrics identify the Milestone Letters better than metrics based on the citation count, which suggests that the structure of the citation network contains information that can be used to improve the ranking of scientific publications. The methods and results presented here are relevant for all evolving systems where network centrality metrics are applied, for example the World Wide Web and online social networks. An interactive Web platform where it is possible to view the ranking of the APS papers by rescaled PageRank is available at the address http://www.sciencenow.info.

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  • Mariani, Manuel Sebastian & Medo, Matúš & Zhang, Yi-Cheng, 2016. "Identification of milestone papers through time-balanced network centrality," Journal of Informetrics, Elsevier, vol. 10(4), pages 1207-1223.
  • Handle: RePEc:eee:infome:v:10:y:2016:i:4:p:1207-1223
    DOI: 10.1016/j.joi.2016.10.005
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    as
    1. Reinhard Werner, 2015. "The focus on bibliometrics makes papers less useful," Nature, Nature, vol. 517(7534), pages 245-245, January.
    2. Jean-Francois Molinari & Alain Molinari, 2008. "A new methodology for ranking scientific institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(1), pages 163-174, April.
    3. Nykl, Michal & Ježek, Karel & Fiala, Dalibor & Dostal, Martin, 2014. "PageRank variants in the evaluation of citation networks," Journal of Informetrics, Elsevier, vol. 8(3), pages 683-692.
    4. Radicchi, Filippo & Castellano, Claudio, 2012. "Testing the fairness of citation indicators for comparison across scientific domains: The case of fractional citation counts," Journal of Informetrics, Elsevier, vol. 6(1), pages 121-130.
    5. Fiala, Dalibor, 2012. "Time-aware PageRank for bibliographic networks," Journal of Informetrics, Elsevier, vol. 6(3), pages 370-388.
    6. Kaur, Jasleen & Radicchi, Filippo & Menczer, Filippo, 2013. "Universality of scholarly impact metrics," Journal of Informetrics, Elsevier, vol. 7(4), pages 924-932.
    7. Chen, P. & Xie, H. & Maslov, S. & Redner, S., 2007. "Finding scientific gems with Google’s PageRank algorithm," Journal of Informetrics, Elsevier, vol. 1(1), pages 8-15.
    8. Juan A Crespo & Ignacio Ortuño-Ortín & Javier Ruiz-Castillo, 2012. "The Citation Merit of Scientific Publications," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-9, November.
    9. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    10. Daniel Sarewitz, 2016. "The pressure to publish pushes down quality," Nature, Nature, vol. 533(7602), pages 147-147, May.
    11. Liebowitz, S J & Palmer, J P, 1984. "Assessing the Relative Impacts of Economic Journals," Journal of Economic Literature, American Economic Association, vol. 22(1), pages 77-88, March.
    12. Jingfeng Xia & Jennifer L. Harmon & Kevin G. Connolly & Ryan M. Donnelly & Mary R. Anderson & Heather A. Howard, 2015. "Who publishes in “predatory” journals?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(7), pages 1406-1417, July.
    13. Richard Van Noorden, 2010. "Metrics: A profusion of measures," Nature, Nature, vol. 465(7300), pages 864-866, June.
    14. Anthony F. J. van Raan, 2005. "Fatal attraction: Conceptual and methodological problems in the ranking of universities by bibliometric methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 62(1), pages 133-143, January.
    15. Peter Weingart, 2005. "Impact of bibliometrics upon the science system: Inadvertent consequences?," Scientometrics, Springer;Akadémiai Kiadó, vol. 62(1), pages 117-131, January.
    16. David A. King, 2004. "The scientific impact of nations," Nature, Nature, vol. 430(6997), pages 311-316, July.
    17. Erjia Yan & Ying Ding, 2009. "Applying centrality measures to impact analysis: A coauthorship network analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 2107-2118, October.
    18. Dunaiski, Marcel & Visser, Willem & Geldenhuys, Jaco, 2016. "Evaluating paper and author ranking algorithms using impact and contribution awards," Journal of Informetrics, Elsevier, vol. 10(2), pages 392-407.
    19. Filippo Radicchi & Claudio Castellano, 2012. "A Reverse Engineering Approach to the Suppression of Citation Biases Reveals Universal Properties of Citation Distributions," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-9, March.
    20. Parolo, Pietro Della Briotta & Pan, Raj Kumar & Ghosh, Rumi & Huberman, Bernardo A. & Kaski, Kimmo & Fortunato, Santo, 2015. "Attention decay in science," Journal of Informetrics, Elsevier, vol. 9(4), pages 734-745.
    21. Diana Hicks & Paul Wouters & Ludo Waltman & Sarah de Rijcke & Ismael Rafols, 2015. "Bibliometrics: The Leiden Manifesto for research metrics," Nature, Nature, vol. 520(7548), pages 429-431, April.
    22. González-Pereira, Borja & Guerrero-Bote, Vicente P. & Moya-Anegón, Félix, 2010. "A new approach to the metric of journals’ scientific prestige: The SJR indicator," Journal of Informetrics, Elsevier, vol. 4(3), pages 379-391.
    23. James Wilsdon, 2015. "We need a measured approach to metrics," Nature, Nature, vol. 523(7559), pages 129-129, July.
    24. Kaur, Jasleen & Ferrara, Emilio & Menczer, Filippo & Flammini, Alessandro & Radicchi, Filippo, 2015. "Quality versus quantity in scientific impact," Journal of Informetrics, Elsevier, vol. 9(4), pages 800-808.
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