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Sequence analysis of annually normalized citation counts: an empirical analysis based on the characteristic scores and scales (CSS) method

Author

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  • Lutz Bornmann

    (Administrative Headquarters of the Max Planck Society)

  • Adam Y. Ye

    (Peking University)

  • Fred Y. Ye

    (Nanjing University)

Abstract

In bibliometrics, only a few publications have focused on the citation histories of publications, where the citations for each citing year are assessed. In this study, therefore, annual categories of field- and time-normalized citation scores (based on the characteristic scores and scales method: 0 = poorly cited, 1 = fairly cited, 2 = remarkably cited, and 3 = outstandingly cited) are used to study the citation histories of papers. As our dataset, we used all articles published in 2000 and their annual citation scores until 2015. We generated annual sequences of citation scores (e.g., $$\left\{ {01233233221} \right\}$$ 01233233221 ) and compared the sequences of annual citation scores of six broader fields (natural sciences, engineering and technology, medical and health sciences, agricultural sciences, social sciences, and humanities). In agreement with previous studies, our results demonstrate that sequences with poorly cited (0) and fairly cited (1) elements dominate the publication set; sequences with remarkably cited (3) and outstandingly cited (4) periods are rare. The highest percentages of constantly poorly cited papers can be found in the social sciences; the lowest percentages are in the agricultural sciences and humanities. The largest group of papers with remarkably cited (3) and/or outstandingly cited (4) periods shows an increasing impact over the citing years with the following orders of sequences: $$\left\{ {0123} \right\}$$ 0123 (6.01%), which is followed by $$\left\{ {123} \right\}$$ 123 (1.62%). Only 0.11% of the papers (n = 909) are constantly on the outstandingly cited level.

Suggested Citation

  • Lutz Bornmann & Adam Y. Ye & Fred Y. Ye, 2017. "Sequence analysis of annually normalized citation counts: an empirical analysis based on the characteristic scores and scales (CSS) method," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1665-1680, December.
  • Handle: RePEc:spr:scient:v:113:y:2017:i:3:d:10.1007_s11192-017-2521-9
    DOI: 10.1007/s11192-017-2521-9
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    References listed on IDEAS

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    1. Lutz Bornmann & Wolfgang Glänzel, 2017. "Applying the CSS method to bibliometric indicators used in (university) rankings," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 1077-1079, February.
    2. Pedro Albarrán & Javier Ruiz‐Castillo, 2011. "References made and citations received by scientific articles," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(1), pages 40-49, January.
    3. Lutz Bornmann & Werner Marx, 2014. "The wisdom of citing scientists," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(6), pages 1288-1292, June.
    4. Christopher Carroll, 2016. "Measuring academic research impact: creating a citation profile using the conceptual framework for implementation fidelity as a case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1329-1340, November.
    5. Li, Yunrong & Radicchi, Filippo & Castellano, Claudio & Ruiz-Castillo, Javier, 2013. "Quantitative evaluation of alternative field normalization procedures," Journal of Informetrics, Elsevier, vol. 7(3), pages 746-755.
    6. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    7. 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.
    8. Christian Brzinsky-Fay & Ulrich Kohler & Magdalena Luniak, 2006. "Sequence analysis with Stata," Stata Journal, StataCorp LP, vol. 6(4), pages 435-460, December.
    9. Bornmann, Lutz & Daniel, Hans-Dieter, 2010. "Citation speed as a measure to predict the attention an article receives: An investigation of the validity of editorial decisions at Angewandte Chemie International Edition," Journal of Informetrics, Elsevier, vol. 4(1), pages 83-88.
    10. Colavizza, Giovanni & Franceschet, Massimo, 2016. "Clustering citation histories in the Physical Review," Journal of Informetrics, Elsevier, vol. 10(4), pages 1037-1051.
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    12. Susanne E. Baumgartner & Loet Leydesdorff, 2014. "Group-based trajectory modeling (GBTM) of citations in scholarly literature: Dynamic qualities of “transient” and “sticky knowledge claims”," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 797-811, April.
    13. Small, Henry & Tseng, Hung & Patek, Mike, 2017. "Discovering discoveries: Identifying biomedical discoveries using citation contexts," Journal of Informetrics, Elsevier, vol. 11(1), pages 46-62.
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    Cited by:

    1. Alonso Rodríguez-Navarro & Ricardo Brito, 2019. "Probability and expected frequency of breakthroughs: basis and use of a robust method of research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 213-235, April.
    2. Andreas Thor & Lutz Bornmann & Werner Marx & Rüdiger Mutz, 2018. "Identifying single influential publications in a research field: new analysis opportunities of the CRExplorer," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 591-608, July.
    3. Guoqiang Liang & Haiyan Hou & Xiaodan Lou & Zhigang Hu, 2019. "Qualifying threshold of “take-off” stage for successfully disseminated creative ideas," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1193-1208, September.
    4. József Popp & Péter Balogh & Judit Oláh & Sebastian Kot & Mónika Harangi Rákos & Péter Lengyel, 2018. "Social Network Analysis of Scientific Articles Published by Food Policy," Sustainability, MDPI, vol. 10(3), pages 1-20, February.
    5. Bornmann, Lutz & Adams, Jonathan & Leydesdorff, Loet, 2018. "The negative effects of citing with a national orientation in terms of recognition: National and international citations in natural-sciences papers from Germany, the Netherlands, and the UK," Journal of Informetrics, Elsevier, vol. 12(3), pages 931-949.

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