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On the interplay between normalisation, bias, and performance of paper impact metrics

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  • Dunaiski, Marcel
  • Geldenhuys, Jaco
  • Visser, Willem

Abstract

We evaluate article-level metrics along two dimensions. Firstly, we analyse metrics’ ranking bias in terms of fields and time. Secondly, we evaluate their performance based on test data that consists of (1) papers that have won high-impact awards and (2) papers that have won prizes for outstanding quality. We consider different citation impact indicators and indirect ranking algorithms in combination with various normalisation approaches (mean-based, percentile-based, co-citation-based, and post hoc rescaling). We execute all experiments on two publication databases which use different field categorisation schemes (author-chosen concept categories and categories based on papers’ semantic information).

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  • Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "On the interplay between normalisation, bias, and performance of paper impact metrics," Journal of Informetrics, Elsevier, vol. 13(1), pages 270-290.
    • Handle: RePEc:eee:infome:v:13:y:2019:i:1:p:270-290
    DOI: 10.1016/j.joi.2019.01.003
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    as
    1. Herranz, Neus & Ruiz-Castillo, Javier, 2012. "Sub-field normalization in the multiplicative case: Average-based citation indicators," Journal of Informetrics, Elsevier, vol. 6(4), pages 543-556.
    2. Loet Leydesdorff & Lutz Bornmann & Rüdiger Mutz & Tobias Opthof, 2011. "Turning the tables on citation analysis one more time: Principles for comparing sets of documents," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(7), pages 1370-1381, July.
    3. A Cecile J W Janssens & Michael Goodman & Kimberly R Powell & Marta Gwinn, 2017. "A critical evaluation of the algorithm behind the Relative Citation Ratio (RCR)," PLOS Biology, Public Library of Science, vol. 15(10), pages 1-5, October.
    4. 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.
    5. Benjamin M. Althouse & Jevin D. West & Carl T. Bergstrom & Theodore Bergstrom, 2009. "Differences in impact factor across fields and over time," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(1), pages 27-34, January.
    6. Bornmann, Lutz & Leydesdorff, Loet & Mutz, Rüdiger, 2013. "The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits," Journal of Informetrics, Elsevier, vol. 7(1), pages 158-165.
    7. Neus Herranz & Javier Ruiz-Castillo, 2012. "Sub-field normalization in the multiplicative case: High- and low-impact citation indicators," Research Evaluation, Oxford University Press, vol. 21(2), pages 113-125, April.
    8. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "The skewness of science in 219 sub-fields and a number of aggregates," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 385-397, August.
    9. Smolinsky, Lawrence, 2016. "Expected number of citations and the crown indicator," Journal of Informetrics, Elsevier, vol. 10(1), pages 43-47.
    10. Anne-Wil Harzing & Satu Alakangas, 2017. "Microsoft Academic: is the phoenix getting wings?," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 371-383, January.
    11. Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
    12. 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.
    13. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2018. "How to evaluate rankings of academic entities using test data," Journal of Informetrics, Elsevier, vol. 12(3), pages 631-655.
    14. Waltman, Ludo & van Eck, Nees Jan & van Leeuwen, Thed N. & Visser, Martijn S. & van Raan, Anthony F.J., 2011. "Towards a new crown indicator: Some theoretical considerations," Journal of Informetrics, Elsevier, vol. 5(1), pages 37-47.
    15. Anne-Wil Harzing & Satu Alakangas, 2017. "Microsoft Academic is one year old: the Phoenix is ready to leave the nest," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1887-1894, September.
    16. Ludo Waltman & Erjia Yan & Nees Jan Eck, 2011. "A recursive field-normalized bibliometric performance indicator: an application to the field of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 301-314, October.
    17. 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.
    18. Sven E. Hug & Michael Ochsner & Martin P. Brändle, 2017. "Citation analysis with microsoft academic," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 371-378, April.
    19. B Ian Hutchins & Xin Yuan & James M Anderson & George M Santangelo, 2016. "Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level," PLOS Biology, Public Library of Science, vol. 14(9), pages 1-25, September.
    20. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    21. Thed N. van Leeuwen & Clara Calero Medina, 2012. "Redefining the field of economics: Improving field normalization for the application of bibliometric techniques in the field of economics," Research Evaluation, Oxford University Press, vol. 21(1), pages 61-70, February.
    22. Sven E. Hug & Martin P. Brändle, 2017. "The coverage of Microsoft Academic: analyzing the publication output of a university," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1551-1571, December.
    23. Bornmann, Lutz & Marx, Werner, 2015. "Methods for the generation of normalized citation impact scores in bibliometrics: Which method best reflects the judgements of experts?," Journal of Informetrics, Elsevier, vol. 9(2), pages 408-418.
    24. Ludo Waltman & Nees Jan Eck & Thed N. Leeuwen & Martijn S. Visser & Anthony F. J. Raan, 2011. "Towards a new crown indicator: an empirical analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 467-481, June.
    25. Jonathan Adams & Karen Gurney & Louise Jackson, 2008. "Calibrating the zoom — a test of Zitt’s hypothesis," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(1), pages 81-95, April.
    26. Bornmann, Lutz & Marx, Werner, 2018. "Critical rationalism and the search for standard (field-normalized) indicators in bibliometrics," Journal of Informetrics, Elsevier, vol. 12(3), pages 598-604.
    27. Michel Zitt & Suzy Ramanana-Rahary & Elise Bassecoulard, 2005. "Relativity of citation performance and excellence measures: From cross-field to cross-scale effects of field-normalisation," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(2), pages 373-401, April.
    28. Silva, F.N. & Rodrigues, F.A. & Oliveira, O.N. & da F. Costa, L., 2013. "Quantifying the interdisciplinarity of scientific journals and fields," Journal of Informetrics, Elsevier, vol. 7(2), pages 469-477.
    29. 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.
    30. John P A Ioannidis & Kevin Boyack & Paul F Wouters, 2016. "Citation Metrics: A Primer on How (Not) to Normalize," PLOS Biology, Public Library of Science, vol. 14(9), pages 1-7, September.
    31. Lundberg, Jonas, 2007. "Lifting the crown—citation z-score," Journal of Informetrics, Elsevier, vol. 1(2), pages 145-154.
    32. 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.
    33. Ludo Waltman & Nees Jan van Eck & Anthony F. J. van Raan, 2012. "Universality of citation distributions revisited," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 72-77, January.
    34. Vaccario, Giacomo & Medo, Matúš & Wider, Nicolas & Mariani, Manuel Sebastian, 2017. "Quantifying and suppressing ranking bias in a large citation network," Journal of Informetrics, Elsevier, vol. 11(3), pages 766-782.
    35. Colliander, Cristian & Ahlgren, Per, 2011. "The effects and their stability of field normalization baseline on relative performance with respect to citation impact: A case study of 20 natural science departments," Journal of Informetrics, Elsevier, vol. 5(1), pages 101-113.
    36. Ludo Waltman & Nees Jan van Eck & Anthony F. J. van Raan, 2012. "Universality of citation distributions revisited," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(1), pages 72-77, January.
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    3. Wang, Jingjing & Xu, Shuqi & Mariani, Manuel S. & Lü, Linyuan, 2021. "The local structure of citation networks uncovers expert-selected milestone papers," Journal of Informetrics, Elsevier, vol. 15(4).

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