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Quantifying perceived impact of scientific publications

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  • Radicchi, Filippo
  • Weissman, Alexander
  • Bollen, Johan

Abstract

We report on an empirical verification of the degree to which citation numbers represent scientific impact as it is actually perceived by experts in their respective field. We run a survey of about 2000 corresponding authors who performed a pairwise impact assessment task across more than 20,000 scientific articles. Results of the survey show that citation data and perceived impact do not align well, unless one properly accounts for psychological biases that affect the opinions of experts with respect to their own papers vs. those of others. Researchers tend to prefer their own publications to the most cited papers in their field of research. There is only a mild positive correlation between the number of citations of top-cited papers and expert preference in pairwise comparisons. This also applies to pairs of papers with several orders of magnitude differences in their total number of accumulated citations. However, when researchers were asked to choose among pairs of their own papers, thus eliminating the bias favouring one's own papers over those of others, they did systematically prefer the most cited article. We conclude that, when scientists have full information and are making unbiased choices, expert opinion on impact is congruent with citation numbers.

Suggested Citation

  • Radicchi, Filippo & Weissman, Alexander & Bollen, Johan, 2017. "Quantifying perceived impact of scientific publications," Journal of Informetrics, Elsevier, vol. 11(3), pages 704-712.
  • Handle: RePEc:eee:infome:v:11:y:2017:i:3:p:704-712
    DOI: 10.1016/j.joi.2017.05.010
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    1. Lutz Bornmann & Gerlind Wallon & Anna Ledin, 2008. "Does the Committee Peer Review Select the Best Applicants for Funding? An Investigation of the Selection Process for Two European Molecular Biology Organization Programmes," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-11, October.
    2. Stefan Hornbostel & Susan Böhmer & Bernd Klingsporn & Jörg Neufeld & Markus Ins, 2009. "Funding of young scientist and scientific excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(1), pages 171-190, April.
    3. M.H. MacRoberts & B.R. MacRoberts, 2010. "Problems of citation analysis: A study of uncited and seldom-cited influences," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(1), pages 1-12, January.
    4. M.H. MacRoberts & B.R. MacRoberts, 2010. "Problems of citation analysis: A study of uncited and seldom‐cited influences," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(1), pages 1-12, January.
    5. Jelke Bethlehem, 2010. "Selection Bias in Web Surveys," International Statistical Review, International Statistical Institute, vol. 78(2), pages 161-188, August.
    6. Richard Van Noorden, 2010. "Metrics: A profusion of measures," Nature, Nature, vol. 465(7300), pages 864-866, June.
    7. Lutz Bornmann & Rüdiger Mutz & Werner Marx & Hermann Schier & Hans‐Dieter Daniel, 2011. "A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 857-879, October.
    8. Johan Bollen & Herbert Van de Sompel & Aric Hagberg & Ryan Chute, 2009. "A Principal Component Analysis of 39 Scientific Impact Measures," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-11, June.
    9. Lutz Bornmann & Hans-Dieter Daniel, 2006. "Selecting scientific excellence through committee peer review - A citation analysis of publications previously published to approval or rejection of post-doctoral research fellowship applicants," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 427-440, September.
    10. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
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    Cited by:

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    3. Teplitskiy, Misha & Duede, Eamon & Menietti, Michael & Lakhani, Karim R., 2022. "How status of research papers affects the way they are read and cited," Research Policy, Elsevier, vol. 51(4).
    4. Kiran Sharma & Parul Khurana, 2021. "Growth and dynamics of Econophysics: a bibliometric and network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4417-4436, May.
    5. Duede, Eamon & Teplitskiy, Misha & Lakhani, Karim & Evans, James, 2024. "Being together in place as a catalyst for scientific advance," Research Policy, Elsevier, vol. 53(2).
    6. Guoliang Lyu & Ganwei Shi, 2019. "On an approach to boosting a journal’s citation potential," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1387-1409, September.
    7. Jiang, Zhuoren & Lin, Tianqianjin & Huang, Cui, 2023. "Deep representation learning of scientific paper reveals its potential scholarly impact," Journal of Informetrics, Elsevier, vol. 17(1).
    8. Zhiya Zuo & Kang Zhao, 2021. "Understanding and predicting future research impact at different career stages—A social network perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 454-472, April.

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