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Quantifying the higher-order influence of scientific publications

Author

Listed:
  • Massimo Franceschet

    (University of Udine)

  • Giovanni Colavizza

    (University of Amsterdam)

Abstract

Citation impact is commonly assessed using direct, first-order citation relations. We consider here instead the indirect influence of publications on new publications via citations. We present a novel method to quantify the higher-order citation influence of publications, considering both direct, or first-order, and indirect, or higher-order citations. In particular, we are interested in higher-order citation influence at the level of disciplines. We apply this method to the whole Web of Science data at the level of disciplines. We find that a significant amount of influence—42%—stems from higher-order citations. Furthermore, we show that higher-order citation influence is helpful to quantify and visualize citation flows among disciplines, and to assess their degree of interdisciplinarity.

Suggested Citation

  • Massimo Franceschet & Giovanni Colavizza, 2020. "Quantifying the higher-order influence of scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 951-963, November.
  • Handle: RePEc:spr:scient:v:125:y:2020:i:2:d:10.1007_s11192-020-03580-9
    DOI: 10.1007/s11192-020-03580-9
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    References listed on IDEAS

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    1. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
    2. van Eck, Nees Jan & Waltman, Ludo, 2014. "CitNetExplorer: A new software tool for analyzing and visualizing citation networks," Journal of Informetrics, Elsevier, vol. 8(4), pages 802-823.
    3. Alexis-Michel Mugabushaka & Anthi Kyriakou & Theo Papazoglou, 2016. "Bibliometric indicators of interdisciplinarity: the potential of the Leinster–Cobbold diversity indices to study disciplinary diversity," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 593-607, May.
    4. Werner Marx & Lutz Bornmann & Andreas Barth & Loet Leydesdorff, 2014. "Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 751-764, April.
    5. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    6. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    7. Alfredo Yegros-Yegros & Ismael Rafols & Pablo D’Este, 2015. "Does Interdisciplinary Research Lead to Higher Citation Impact? The Different Effect of Proximal and Distal Interdisciplinarity," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-21, August.
    8. Eugene Garfield & A. I. Pudovkin & V. S. Istomin, 2003. "Why do we need algorithmic historiography?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 400-412, March.
    9. repec:nas:journl:v:115:y:2018:p:3308-3313 is not listed on IDEAS
    10. Alan L. Porter & Ismael Rafols, 2009. "Is science becoming more interdisciplinary? Measuring and mapping six research fields over time," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 719-745, December.
    11. Yi-Ning Tu & Shu-Lan Hsu, 2016. "Constructing conceptual trajectory maps to trace the development of research fields," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(8), pages 2016-2031, August.
    12. Thor, Andreas & Marx, Werner & Leydesdorff, Loet & Bornmann, Lutz, 2016. "Introducing CitedReferencesExplorer (CRExplorer): A program for reference publication year spectroscopy with cited references standardization," Journal of Informetrics, Elsevier, vol. 10(2), pages 503-515.
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