IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v120y2019i1d10.1007_s11192-019-03113-z.html
   My bibliography  Save this article

Disruptive papers published in Scientometrics

Author

Listed:
  • Lutz Bornmann

    (Administrative Headquarters of the Max Planck Society)

  • Alexander Tekles

    (Administrative Headquarters of the Max Planck Society
    Ludwig-Maximilians-University Munich)

Abstract

Wu et al. (Nature 566:378–382, 2019. https://doi.org/10.1038/s41586-019-0941-9 ) recently proposed a new, citation-based index of ‘disruptiveness’ that is based on a dynamic network measure of technological change. In this study, we present and discuss papers published in Scientometrics between 2000 and 2010 with the highest (positive) disruption index.

Suggested Citation

  • Lutz Bornmann & Alexander Tekles, 2019. "Disruptive papers published in Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 331-336, July.
    • Handle: RePEc:spr:scient:v:120:y:2019:i:1:d:10.1007_s11192-019-03113-z
    DOI: 10.1007/s11192-019-03113-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03113-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-019-03113-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Russell J. Funk & Jason Owen-Smith, 2017. "A Dynamic Network Measure of Technological Change," Management Science, INFORMS, vol. 63(3), pages 791-817, March.
    2. Marc Bertin & Iana Atanassova & Cassidy R. Sugimoto & Vincent Lariviere, 2016. "The linguistic patterns and rhetorical structure of citation context: an approach using n-grams," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1417-1434, December.
    3. Maria Bordons & M. T. Fernández & Isabel Gómez, 2002. "Advantages and limitations in the use of impact factor measures for the assessment of research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(2), pages 195-206, February.
    4. 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.
    5. Small, Henry, 2018. "Characterizing highly cited method and non-method papers using citation contexts: The role of uncertainty," Journal of Informetrics, Elsevier, vol. 12(2), pages 461-480.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin, Yiling & Evans, James A. & Wu, Lingfei, 2022. "New directions in science emerge from disconnection and discord," Journal of Informetrics, Elsevier, vol. 16(1).
    2. Bornmann, Lutz & Tekles, Alexander, 2021. "Convergent validity of several indicators measuring disruptiveness with milestone assignments to physics papers by experts," Journal of Informetrics, Elsevier, vol. 15(3).
    3. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    4. Nan Deng & An Zeng, 2023. "Enhancing the robustness of the disruption metric against noise," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2419-2428, April.
    5. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.
    6. Naudé, Wim, 2024. "Is the Scholarly Field of Entrepreneurship at Its End?," IZA Discussion Papers 16916, Institute of Labor Economics (IZA).
    7. Ruijie Wang & Yuhao Zhou & An Zeng, 2023. "Evaluating scientists by citation and disruption of their representative works," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1689-1710, March.
    8. António Osório & Lutz Bornmann, 2021. "On the disruptive power of small-teams research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 117-133, January.
    9. Libo Sheng & Dongqing Lyu & Xuanmin Ruan & Hongquan Shen & Ying Cheng, 2023. "The association between prior knowledge and the disruption of an article," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4731-4751, August.
    10. Yuyan Jiang & Xueli Liu, 2023. "A Bibliometric Analysis and Disruptive Innovation Evaluation for the Field of Energy Security," Sustainability, MDPI, vol. 15(2), pages 1-29, January.
    11. Bethânia Ávila Rodrigues & Mariana Machado Fidelis Nascimento & Juliana Vitória Messias Bittencourt, 2021. "Mapping of the behavior of scientific publications since the decade of 1990 until the present day in the field of food and nutrition security," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2459-2483, March.
    12. Lutz Bornmann & Sitaram Devarakonda & Alexander Tekles & George Chacko, 2020. "Disruptive papers published in Scientometrics: meaningful results by using an improved variant of the disruption index originally proposed by Wu, Wang, and Evans (2019)," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1149-1155, May.
    13. Leydesdorff, Loet & Bornmann, Lutz, 2021. "Disruption indices and their calculation using web-of-science data: Indicators of historical developments or evolutionary dynamics?," Journal of Informetrics, Elsevier, vol. 15(4).
    14. Ruan, Xuanmin & Lyu, Dongqing & Gong, Kaile & Cheng, Ying & Li, Jiang, 2021. "Rethinking the disruption index as a measure of scientific and technological advances," Technological Forecasting and Social Change, Elsevier, vol. 172(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Min, Chao & Bu, Yi & Sun, Jianjun, 2021. "Predicting scientific breakthroughs based on knowledge structure variations," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    2. Leydesdorff, Loet & Bornmann, Lutz, 2021. "Disruption indices and their calculation using web-of-science data: Indicators of historical developments or evolutionary dynamics?," Journal of Informetrics, Elsevier, vol. 15(4).
    3. Lutz Bornmann & K. Brad Wray & Robin Haunschild, 2020. "Citation concept analysis (CCA): a new form of citation analysis revealing the usefulness of concepts for other researchers illustrated by exemplary case studies including classic books by Thomas S. K," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1051-1074, February.
    4. Qu, Guannan & Chen, Jin & Zhang, Ruhao & Wang, Luyao & Yang, Yayu, 2023. "Technological search strategy and breakthrough innovation: An integrated approach based on main-path analysis," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Liu, Meijun & Jaiswal, Ajay & Bu, Yi & Min, Chao & Yang, Sijie & Liu, Zhibo & Acuña, Daniel & Ding, Ying, 2022. "Team formation and team impact: The balance between team freshness and repeat collaboration," Journal of Informetrics, Elsevier, vol. 16(4).
    6. Yiling Lin & Carl Benedikt Frey & Lingfei Wu, 2022. "Remote Collaboration Fuses Fewer Breakthrough Ideas," Papers 2206.01878, arXiv.org, revised Oct 2023.
    7. Bornmann, Lutz & Tekles, Alexander, 2021. "Convergent validity of several indicators measuring disruptiveness with milestone assignments to physics papers by experts," Journal of Informetrics, Elsevier, vol. 15(3).
    8. Yanbo Zhou & Xin-Li Xu & Xu-Hua Yang & Qu Li, 2022. "The influence of disruption on evaluating the scientific significance of papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5931-5945, October.
    9. Ruan, Xuanmin & Lyu, Dongqing & Gong, Kaile & Cheng, Ying & Li, Jiang, 2021. "Rethinking the disruption index as a measure of scientific and technological advances," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    10. Jiexun Li & Jiyao Chen, 2022. "Measuring destabilization and consolidation in scientific knowledge evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5819-5839, October.
    11. Ruijie Wang & Yuhao Zhou & An Zeng, 2023. "Evaluating scientists by citation and disruption of their representative works," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1689-1710, March.
    12. Seolmin Yang & So Young Kim, 2023. "Knowledge-integrated research is more disruptive when supported by homogeneous funding sources: a case of US federally funded research in biomedical and life sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3257-3282, June.
    13. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    14. Dangzhi Zhao & Andreas Strotmann, 2020. "Deep and narrow impact: introducing location filtered citation counting," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 503-517, January.
    15. Libo Sheng & Dongqing Lyu & Xuanmin Ruan & Hongquan Shen & Ying Cheng, 2023. "The association between prior knowledge and the disruption of an article," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4731-4751, August.
    16. Michael Park & Erin Leahey & Russell Funk, 2021. "The decline of disruptive science and technology," Papers 2106.11184, arXiv.org, revised Jul 2022.
    17. Lutz Bornmann & Sitaram Devarakonda & Alexander Tekles & George Chacko, 2020. "Disruptive papers published in Scientometrics: meaningful results by using an improved variant of the disruption index originally proposed by Wu, Wang, and Evans (2019)," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1149-1155, May.
    18. 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.
    19. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
    20. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:120:y:2019:i:1:d:10.1007_s11192-019-03113-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.