IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i10d10.1007_s11192-022-04501-8.html
   My bibliography  Save this article

Awakening sleeping beauties during the COVID-19 pandemic influences the citation impact of their references

Author

Listed:
  • Houcemeddine Turki

    (University of Sfax)

  • Mohamed Ali Hadj Taieb

    (University of Sfax)

  • Mohamed Ben Aouicha

    (University of Sfax)

Abstract

In this research letter, we build upon recent studies about the sleeping beauties awakened by the COVID-19 pandemic. We prove that a peak of citations for sleeping beauties is associated with a sharp increase in the number of citations received by their references. This demonstrates the existence of a cascading activation of citation-based sleeping beauties.

Suggested Citation

  • Houcemeddine Turki & Mohamed Ali Hadj Taieb & Mohamed Ben Aouicha, 2022. "Awakening sleeping beauties during the COVID-19 pandemic influences the citation impact of their references," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 6047-6050, October.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:10:d:10.1007_s11192-022-04501-8
    DOI: 10.1007/s11192-022-04501-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04501-8
    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/s11192-022-04501-8?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. Yang, Jinqing & Bu, Yi & Lu, Wei & Huang, Yong & Hu, Jiming & Huang, Shengzhi & Zhang, Li, 2022. "Identifying keyword sleeping beauties: A perspective on the knowledge diffusion process," Journal of Informetrics, Elsevier, vol. 16(1).
    2. Kehan Wang & Wenxuan Shi & Junsong Bai & Xiaoping Zhao & Liying Zhang, 2021. "Prediction and application of article potential citations based on nonlinear citation-forecasting combined model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6533-6550, August.
    3. Lin, Yiling & Evans, James A. & Wu, Lingfei, 2022. "New directions in science emerge from disconnection and discord," Journal of Informetrics, Elsevier, vol. 16(1).
    4. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    5. You Song & Fangling Situ & Hongjun Zhu & Jinzhi Lei, 2018. "To be the Prince to wake up Sleeping Beauty: the rediscovery of the delayed recognition studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 9-24, October.
    6. Milad Haghani & Pegah Varamini, 2021. "Temporal evolution, most influential studies and sleeping beauties of the coronavirus literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7005-7050, August.
    7. Yi Zhang & Xiaojing Cai & Caroline V. Fry & Mengjia Wu & Caroline S. Wagner, 2021. "Topic evolution, disruption and resilience in early COVID-19 research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4225-4253, May.
    Full references (including those not matched with items on IDEAS)

    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. Chi, Yuxue & Tang, Xianyi & Liu, Yijun, 2022. "Exploring the “awakening effect” in knowledge diffusion: a case study of publications in the library and information science domain," Journal of Informetrics, Elsevier, vol. 16(4).
    2. Jianhua Hou & Hao Li & Yang Zhang, 2023. "Altmetrics-based sleeping beauties: necessity or just a supplement?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5477-5506, October.
    3. Peter Kokol & Helena Blažun Vošner & Jernej Završnik & Grega Žlahtič, 2022. "Sleeping beauties in health informatics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 5073-5081, August.
    4. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    5. Jianhua Hou & Xiucai Yang & Yang Zhang, 2023. "The effect of social media knowledge cascade: an analysis of scientific papers diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5169-5195, September.
    6. Hui Fang, 2019. "A transition stage co-citation criterion for identifying the awakeners of sleeping beauty publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 307-322, October.
    7. Wu, Lingfei & Kittur, Aniket & Youn, Hyejin & Milojević, Staša & Leahey, Erin & Fiore, Stephen M. & Ahn, Yong-Yeol, 2022. "Metrics and mechanisms: Measuring the unmeasurable in the science of science," Journal of Informetrics, Elsevier, vol. 16(2).
    8. Zhentao Liang & Jin Mao & Kun Lu & Gang Li, 2021. "Finding citations for PubMed: a large-scale comparison between five freely available bibliographic data sources," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9519-9542, December.
    9. Yue Wang & Ning Li & Bin Zhang & Qian Huang & Jian Wu & Yang Wang, 2023. "The effect of structural holes on producing novel and disruptive research in physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1801-1823, March.
    10. Peter Kokol & Jernej Završnik & Helena Blažun Vošner, 2020. "Did Sleeping Papers in nursing research miss their target audience?," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1243-1248, February.
    11. Yang, Jinqing & Bu, Yi & Lu, Wei & Huang, Yong & Hu, Jiming & Huang, Shengzhi & Zhang, Li, 2022. "Identifying keyword sleeping beauties: A perspective on the knowledge diffusion process," Journal of Informetrics, Elsevier, vol. 16(1).
    12. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.
    13. Zhao, Yi & Liu, Lifan & Zhang, Chengzhi, 2022. "Is coronavirus-related research becoming more interdisciplinary? A perspective of co-occurrence analysis and diversity measure of scientific articles," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    14. Török, Ádám & Konka, Boglárka & Nagy, Andrea Magda, 2023. "A koronavírus-járvány a közgazdasági szakirodalomban. Egy új határterület tudománymetriai elemzése [The coronavirus pandemic in the economics literature. The scientometric analysis of a new discipl," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 284-304.
    15. Jorge A. V. Tohalino & Laura V. C. Quispe & Diego R. Amancio, 2021. "Analyzing the relationship between text features and grants productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4255-4275, May.
    16. 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.
    17. Jianhua Hou & Xiucai Yang & Haoyang Song & Haiyue Yao, 2023. "Will patent family be dormant? Research on the identification and characteristics of sleeping beauty’s patent family," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5361-5387, October.
    18. Hou, Jianhua & Wang, Dongyi & Li, Jing, 2022. "A new method for measuring the originality of academic articles based on knowledge units in semantic networks," Journal of Informetrics, Elsevier, vol. 16(3).
    19. Anthony F. J. van Raan, 2021. "Sleeping beauties gain impact in overdrive mode," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4311-4332, May.
    20. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).

    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:127:y:2022:i:10:d:10.1007_s11192-022-04501-8. 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.