, Volume 117, Issue 1, pp 9–24 | Cite as

To be the Prince to wake up Sleeping Beauty: the rediscovery of the delayed recognition studies

  • You Song
  • Fangling Situ
  • Hongjun Zhu
  • Jinzhi LeiEmail author


In science, sleeping papers, previously known as “Sleeping Beauties”, refer to scientific papers that are recognized by the scientific community after a long hibernation period following their publication. Many factors may contribute to their delayed yet exceptional popularity, such as the introduction of new technologies or ideas that are beyond the capabilities at the time of publication. The recognition of a sleeping paper, often through a paper that cites the sleeping paper and has a profound impact on the research area, is important to the scientific community. Here, we proposed a method to identify the paper that rediscovers a sleeping paper, known as a rediscovering paper, based on the citation network of the sleeping paper. Based on the 15 rediscovering papers obtained from the top sleeping papers in science, we introduced 5 feature indices of the leading authors of these rediscovering papers (rediscovering authors) defined by an academic search system AMiner ( The 5 feature indices depict academic achievements of researchers from various aspects: Publication, Citation, Longevity, H-index and Sociability. The rediscovering authors lead to most general scientific authors in the 5 feature indices. Our results reveal common features of potential rediscovering authors in the scientific community who may play significant roles in the propagation of citation networks.


Sleeping Beauty Bibliometrics Delayed recognition Rediscovering paper Citation network 



This work was supported by the National Natural Science Foundation of China (91430101).


  1. Barber, B. (1961). Resistance by scientists to scientific discovery. Science, 134(3479), 596–602.CrossRefGoogle Scholar
  2. Braun, T., Glänzel, W., & Schubert, A. (2010). On sleeping beauties, princes and other tales of citation distributions. Research Evaluation, 19(3), 195–202.CrossRefGoogle Scholar
  3. Burrell, Q. L. (2005). Are “Sleeping Beauties” to be expected? Scientometrics, 65(3), 381–389.CrossRefGoogle Scholar
  4. Cole, S. (1970). Professional standing and the reception of scientific discoveries. American Journal of Sociology, 76(2), 286–306.CrossRefGoogle Scholar
  5. Costas, R., van Leeuwen, T. N., & van Raan, A. F. (2010). Is scientific literature subject to a ‘sell-by-date’? A general methodology to analyze the ‘durability’of scientific documents. Journal of the Association for Information Science and Technology, 61(2), 329–339.Google Scholar
  6. Davis, P., & Papanek, G. F. (1984). Faculty ratings of major economics departments by citations. The American Economic Review, 74(1), 225–230.Google Scholar
  7. Garfield, E. (1955). Citation indexes for science. Science, 122(3159), 108–111.CrossRefGoogle Scholar
  8. Garfield, E. (1980). Premature discovery or delayed recognition-why. Current Contents, 21, 5–10.Google Scholar
  9. Garfield, E. (1989). Delayed recognition in scientific discovery-citation frequency-analysis aids the search for case-histories. Current Contents, 23, 3–9.Google Scholar
  10. Garfield, E. (1989). More delayed recognition. 1. Examples from the genetics of color-blindness, the entropy of short-term-memory, phosphoinositides, and polymer rheology. Current Contents, 38, 3–8.Google Scholar
  11. Garfield, E. (1990). More delayed recognition. 2. From inhibin to scanning electron-microscopy. Current Contents, 9, 3–9.Google Scholar
  12. Gillespie, D. T. (1977). Exact stochastic simulation of coupled chemical reactions. The Journal of Physical Chemistry, 81(25), 2340–2361.CrossRefGoogle Scholar
  13. Glänzel, W., Schlemmer, B., & Thijs, B. (2003). Better late than never? On the chance to become highly cited only beyond the standard bibliometric time horizon. Scientometrics, 58(3), 571–586.CrossRefGoogle Scholar
  14. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. In Proceedings of the National academy of sciences of the United States of America (pp. 16,569–16,572).Google Scholar
  15. Ke, Q., Ferrara, E., Radicchi, F., & Flammini, A. (2015). Defining and identifying sleeping beauties in science. Proceedings of the National Academy of Sciences, 112(24), 7426–7431.CrossRefGoogle Scholar
  16. Kinney, A. (2007). National scientific facilities and their science impact on nonbiomedical research. Proceedings of the National Academy of Sciences, 104(46), 17943–17947.CrossRefGoogle Scholar
  17. Li, J. (2014). Citation curves of “all-elements-sleeping-beauties” : “Flash in the pan” first and then “delayed recognition”. Scientometrics, 100(2), 595–601.CrossRefGoogle Scholar
  18. Li, J., & Fred, Y. Y. (2016). Distinguishing sleeping beauties in science. Scientometrics, 108(2), 821–828.CrossRefGoogle Scholar
  19. Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences, 101(suppl 1), 5200–5205.CrossRefGoogle Scholar
  20. Ohba, N., & Nakao, K. (2012). Sleeping beauties in ophthalmology. Scientometrics, 93(2), 253–264.CrossRefGoogle Scholar
  21. Radicchi, F., Fortunato, S., & Castellano, C. (2008). Universality of citation distributions: Toward an objective measure of scientific impact. Proceedings of the National Academy of Sciences, 105(45), 17268–17272.CrossRefGoogle Scholar
  22. Stent, G. S. (1972). Prematurity and uniqueness in scientific discovery. Scientific American, 227, 84–93.CrossRefGoogle Scholar
  23. Sugimoto, C. R., & Mostafa, J. (2018). A note of concern and context: On careful use of terminologies. Journal of the Association for Information Science and Technology, 69(3), 347–348.CrossRefGoogle Scholar
  24. Sun, J., Min, C., & Li, J. (2016). A vector for measuring obsolescence of scientific articles. Scientometrics, 107(2), 745–757.CrossRefGoogle Scholar
  25. Sun, X., Kaur, J., Milojević, S., Flammini, A., & Menczer, F. (2013). Social dynamics of science. In Scientific reports (Vol. 3).Google Scholar
  26. Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., & Su, Z. (2008). Arnetminer: Extraction and mining of academic social networks. In KDD’08 (pp. 990–998).Google Scholar
  27. Uzzi, B., Mukherjee, S., Stringer, M., & Jones, B. (2013). Atypical combinations and scientific impact. Science, 342(6157), 468–472.CrossRefGoogle Scholar
  28. Van Dalen, H. P., & Henkens, K. (2005). Signals in science-on the importance of signaling in gaining attention in science. Scientometrics, 64(2), 209–233.CrossRefGoogle Scholar
  29. Van Raan, A. F. (2004). Sleeping beauties in science. Scientometrics, 59(3), 467–472.CrossRefGoogle Scholar
  30. van Raan, A. F. (2015). Dormitory of physical and engineering sciences: Sleeping Beauties may be sleeping innovations. PLoS ONE, 10(10), e0139786.CrossRefGoogle Scholar
  31. Wang, D., Song, C., & Barabási, A. L. (2013). Quantifying long-term scientific impact. Science, 342(6154), 127–132.CrossRefGoogle Scholar
  32. Wyatt, H. (1975). Knowledge and prematurity: The journey from transformation to dna. Perspectives in Biology and Medicine, 18(2), 149–156.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  1. 1.School of SoftwareBeihang UniversityBeijingChina
  2. 2.Zhou Pei-Yuan Center for Applied Mathematics, MOE Key Laboratory of BioinformaticsTsinghua UniversityBeijingChina

Personalised recommendations