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Sleeping beauties in Computer Science: characterization and early identification

Author

Listed:
  • Ratnadeep Dey

    (Indian Institute of Engineering Science and Technology)

  • Anurag Roy

    (Indian Institute of Engineering Science and Technology)

  • Tanmoy Chakraborty

    (Indraprastha Institute of Information Technology (IIIT-D))

  • Saptarshi Ghosh

    (Indian Institute of Technology, Kharagpur)

Abstract

While a large majority of scientific publications get most of their citations within the initial few years after publication, there is an interesting number of papers—termed as sleeping beauties—which do not get much cited for several years after being published, but then suddenly start getting cited heavily. In this work, we focus on sleeping beauties (SBs) in the domain of Computer Science. We identify more than 5,000 sleeping beauties in Computer Science, and characterise them based on their sub-field and their citation profile after awakening. We also reveal some interesting factors which led to their awakening long after publication. Furthermore, we also propose a methodology for early identification of sleeping beauties, and develop a machine learning-based classification approach that attempts to classify publications based on whether they are likely to be SBs. The classifier achieves a precision of 0.73 and a recall of 0.45 in identifying SBs immediately after their year of publications, and the performance significantly improves with time. To our knowledge, this is the first study on sleeping beauties in Computer Science.

Suggested Citation

  • Ratnadeep Dey & Anurag Roy & Tanmoy Chakraborty & Saptarshi Ghosh, 2017. "Sleeping beauties in Computer Science: characterization and early identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1645-1663, December.
    • Handle: RePEc:spr:scient:v:113:y:2017:i:3:d:10.1007_s11192-017-2543-3
    DOI: 10.1007/s11192-017-2543-3
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    References listed on IDEAS

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    Cited by:

    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. 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).
    3. 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.
    4. Elena M. Tur & Evangelos Bourelos & Maureen McKelvey, 2022. "The case of sleeping beauties in nanotechnology: a study of potential breakthrough inventions in emerging technologies," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 69(3), pages 683-708, December.
    5. Miura, Takahiro & Asatani, Kimitaka & Sakata, Ichiro, 2023. "Revisiting the uniformity and inconsistency of slow-cited papers in science," Journal of Informetrics, Elsevier, vol. 17(1).
    6. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    7. 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.
    8. ZhangJian Zong & XuanZhen Liu & Hui Fang, 2018. "Sleeping beauties with no prince based on the co-citation criterion," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1841-1852, December.
    9. Li, Xin & Ma, Xiaodi & Feng, Ye, 2024. "Early identification of breakthrough research from sleeping beauties using machine learning," Journal of Informetrics, Elsevier, vol. 18(2).
    10. 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.
    11. 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.
    12. Minh Nguyen Quang & Tim Rogers & Jan Hofman & Ana B Lanham, 2019. "New framework for automated article selection applied to a literature review of Enhanced Biological Phosphorus Removal," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-42, May.
    13. Du, Jian & Li, Peixin & Haunschild, Robin & Sun, Yinan & Tang, Xiaoli, 2020. "Paper-patent citation linkages as early signs for predicting delayed recognized knowledge: Macro and micro evidence," Journal of Informetrics, Elsevier, vol. 14(2).
    14. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.
    15. Helena H. Zhang & Fred Y. Ye, 2020. "Identifying ‘associated-sleeping-beauties’ in ‘swan-groups’ based on small qualified datasets of physics and economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1525-1537, March.

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