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Revisiting the disruptive index: evidence from the Nobel Prize-winning articles

Author

Listed:
  • Guoqiang Liang

    (Beijing University of Technology)

  • Ying Lou

    (Beijing University of Technology)

  • Haiyan Hou

    (Dalian University of Technology)

Abstract

In the last two decades, scholars have designed various types of bibliographic-related indicators to identify breakthrough-class academic achievements. In this study, we take a step further to look at the performance of the promising disruptive index (DI) in reference (Wu et al. in Nature 566(7744):378-382, https://doi.org/10.1038/s41586-019-0941-9 , 2019), thus deepening our understanding of the DI and further facilitating its wise use in bibliometrics. Using publication records for Nobel laureates between 1900 and 2016, we calculate the DI of Nobel Prize-winning articles and benchmark articles from each year, use the median and mean DI to denote the central tendency in each year, and analyze the variation of the DI since publication. We find that Nobel Prize-winning articles are not necessarily more disruptive than benchmark articles. Results based on DI depend on the length of their citation time window, and different citation time windows may cause different, even controversial, results. As a result, research assessment should balance between short- & long-term scientific impact; Also, discipline and time play a role in the length of the citation window when using DI to measure the innovativeness of scientific work. The study also discusses potential research directions around DI.

Suggested Citation

  • Guoqiang Liang & Ying Lou & Haiyan Hou, 2022. "Revisiting the disruptive index: evidence from the Nobel Prize-winning articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5721-5730, October.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:10:d:10.1007_s11192-022-04499-z
    DOI: 10.1007/s11192-022-04499-z
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    References listed on IDEAS

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    1. Bornmann, Lutz & Tekles, Alexander & Zhang, Helena H. & Ye, Fred Y., 2019. "Do we measure novelty when we analyze unusual combinations of cited references? A validation study of bibliometric novelty indicators based on F1000Prime data," Journal of Informetrics, Elsevier, vol. 13(4).
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    6. Lingfei Wu & Dashun Wang & James A. Evans, 2019. "Large teams develop and small teams disrupt science and technology," Nature, Nature, vol. 566(7744), pages 378-382, February.
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    Cited by:

    1. Adrian Furnham, 2023. "Peer nominations as scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1451-1458, February.
    2. Ao, Weiyi & Lyu, Dongqing & Ruan, Xuanmin & Li, Jiang & Cheng, Ying, 2023. "Scientific creativity patterns in scholars’ academic careers: Evidence from PubMed," Journal of Informetrics, Elsevier, vol. 17(4).
    3. Yuyan Jiang & Xueli Liu, 2023. "A construction and empirical research of the journal disruption index based on open citation data," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 3935-3958, July.
    4. Zhang, Ming-Ze & Wang, Tang-Rong & Lyu, Peng-Hui & Chen, Qi-Mei & Li, Ze-Xia & Ngai, Eric W.T., 2024. "Impact of gender composition of academic teams on disruptive output," Journal of Informetrics, Elsevier, vol. 18(2).

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