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A vector for measuring obsolescence of scientific articles

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  • Jianjun Sun

    (Nanjing University)

  • Chao Min

    (Nanjing University)

  • Jiang Li

    (Zhejiang University)

Abstract

Diachronous studies of obsolescence categorized articles into three general types: “flashes in the pan”, “sleeping beauties” and “normal articles”. These studies used either quartiles or averages to define thresholds on sleeping and awakening periods. However, such average- and quartile-based criteria, sometimes, are less effective in distinguishing “flashes in the pan” and “sleeping beauties” from normal articles due to the arbitrariness of the manner in which thresholds are determined. In this investigation, we propose a vector for measuring obsolescence of scientific articles as an alternative to these criteria. The obsolescence vector is designed as O = (G s, A −), with G s as a parameter affecting the shape of citation curves and A − as a parameter detecting drastic fluctuation of citation curves. We collected 50,789 articles authored by Nobel laureates during 1900–2012. Applying our criteria to this dataset, we compared the obsolescence vector with average- and quartile-based criteria. Our findings show that the proposed obsolescence vector is different from and serves as an alternative to the average- and quartile-based criteria.

Suggested Citation

  • Jianjun Sun & Chao Min & Jiang Li, 2016. "A vector for measuring obsolescence of scientific articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 745-757, May.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1884-7
    DOI: 10.1007/s11192-016-1884-7
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    References listed on IDEAS

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    Cited by:

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    3. Cristina López-Duarte & Marta M. Vidal-Suárez & Belén González-Díaz, 2019. "Cross-national distance and international business: an analysis of the most influential recent models," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 173-208, October.
    4. Jiang Li & Fred Y. Ye, 2016. "Distinguishing sleeping beauties in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 821-828, August.
    5. 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).
    6. 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.
    7. Jianhua Hou & Hao Li & Yang Zhang, 2020. "Identifying the princes base on Altmetrics: An awakening mechanism of sleeping beauties from the perspective of social media," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-28, November.
    8. 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.
    9. Zhichao Fang & Rodrigo Costas, 2020. "Studying the accumulation velocity of altmetric data tracked by Altmetric.com," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1077-1101, May.
    10. 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.
    11. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    12. 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.
    13. 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.
    14. Onodera, Natsuo, 2016. "Properties of an index of citation durability of an article," Journal of Informetrics, Elsevier, vol. 10(4), pages 981-1004.
    15. 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.
    16. 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.
    17. Colavizza, Giovanni & Franceschet, Massimo, 2016. "Clustering citation histories in the Physical Review," Journal of Informetrics, Elsevier, vol. 10(4), pages 1037-1051.
    18. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.
    19. Mingyang Wang & Shi Li & Guangsheng Chen, 2017. "Detecting latent referential articles based on their vitality performance in the latest 2 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1557-1571, September.
    20. 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.

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