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Sleeping beauties in genius work: When were they awakened?

Citations

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Cited by:

  1. Hui Fang, 2018. "Analysing the variation tendencies of the numbers of yearly citations for sleeping beauties in science by using derivative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1051-1070, May.
  2. Meijun Liu & Xiao Hu & Jiang Li, 2018. "Knowledge flow in China’s humanities and social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 607-626, March.
  3. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.
  4. Yang, Yu-Hsiang & Chiang, Yao-Min & Lin, Hung-Lung, 2024. "Sleeping beauties in finance," Research in International Business and Finance, Elsevier, vol. 70(PB).
  5. 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.
  6. Min, Chao & Sun, Jianjun & Pei, Lei & Ding, Ying, 2016. "Measuring delayed recognition for papers: Uneven weighted summation and total citations," Journal of Informetrics, Elsevier, vol. 10(4), pages 1153-1165.
  7. Aurora A. C. Teixeira & Pedro Cosme Vieira & Ana Patrícia Abreu, 2017. "Sleeping Beauties and their princes in innovation studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 541-580, February.
  8. 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).
  9. Meijun Liu & Dongbo Shi & Jiang Li, 2017. "Double-edged sword of interdisciplinary knowledge flow from hard sciences to humanities and social sciences: Evidence from China," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-16, September.
  10. Keye Wu & Ziyue Xie & Jia Tina Du, 2024. "Does science disrupt technology? Examining science intensity, novelty, and recency through patent-paper citations in the pharmaceutical field," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5469-5491, September.
  11. Onodera, Natsuo, 2016. "Properties of an index of citation durability of an article," Journal of Informetrics, Elsevier, vol. 10(4), pages 981-1004.
  12. Zeng, Carl J. & Qi, Eric P. & Li, Simon S. & Stanley, H. Eugene & Ye, Fred Y., 2017. "Statistical characteristics of breakthrough discoveries in science using the metaphor of black and white swans," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 40-46.
  13. Jiang Li & Fred Y. Ye, 2016. "Distinguishing sleeping beauties in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 821-828, August.
  14. 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.
  15. Hu, Zewen & Chen, Yu & Cui, Jingjing, 2025. "Identifying potential sleeping beauties based on dynamic time warping algorithm and citation curve benchmarking," Journal of Informetrics, Elsevier, vol. 19(2).
  16. Chen, Jiyao & Shao, Diana & Fan, Shaokun, 2021. "Destabilization and consolidation: Conceptualizing, measuring, and validating the dual characteristics of technology," Research Policy, Elsevier, vol. 50(1).
  17. Chakraborty, Joyita & Pradhan, Dinesh K. & Nandi, Subrata, 2024. "A multiple k-means cluster ensemble framework for clustering citation trajectories," Journal of Informetrics, Elsevier, vol. 18(2).
  18. 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.
  19. 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).
  20. Wu, Keye & Leng, Rhodri Ivor & Hou, Wanfang, 2026. "Weak ties matter for scientific innovation: The dual perspectives of knowledge recombination network and collaboration network," Journal of Informetrics, Elsevier, vol. 20(1).
  21. Guoqiang Liang & Yaqin Li & Lurui Song & Chaoguang Huo, 2023. "Magnitude decrease of the Matthew effect in citations: a study based on Nobel Prize articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(12), pages 6357-6371, December.
  22. Geng, Yu & Yin, Yixian & Cai, Ruonan & Wang, Xianwen, 2026. "Tracing scientific knowledge flow in patents: An explainable machine learning study of citation types and their temporal dynamics," Journal of Informetrics, Elsevier, vol. 20(1).
  23. Lutz Bornmann & Adam Y. Ye & Fred Y. Ye, 2018. "Identifying “hot papers” and papers with “delayed recognition” in large-scale datasets by using dynamically normalized citation impact scores," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 655-674, August.
  24. Sepideh Fahimifar & Elmira Janavi & Fatemeh Fadaei, 2024. "Awakening the beauty: a journey through dormant gems in strategic management literature," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(4), pages 3331-3362, August.
  25. Anthony F. J. van Raan, 2021. "Sleeping beauties gain impact in overdrive mode," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4311-4332, May.
  26. Liang, Guoqiang & Hou, Haiyan & Ding, Ying & Hu, Zhigang, 2020. "Knowledge recency to the birth of Nobel Prize-winning articles: Gender, career stage, and country," Journal of Informetrics, Elsevier, vol. 14(3).
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