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Identification of referencing and citation processes of scientific journals based on the citation distribution model

Author

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  • Guang Yu

    (Harbin Institute of Technology)

  • Yi-Jun Li

    (Harbin Institute of Technology)

Abstract

In this article, we firstly analyze the referencing process and the citation process of a scientific journal in theory, and find that the observed referencing or citation process includes the diffusing process and the aging process of cited literature and the publishing process of citing literature, thereby it is illuminated why the identified average publication delay $$ \left( {\bar{T} = T_{s} + \tau } \right) $$ was longer than the observed value. Secondly, we compare the transfer function model of the observed citing process with other classical citation distribution models and find that the model is superior to others. Finally, using the model, we identify parameters of actual referencing and citation processes from data of age distributions of references and citations of 38 journals of neurology and applied mathematics in JCR, respectively; and then compare differences of identified parameters and obtain some interesting conclusions.

Suggested Citation

  • Guang Yu & Yi-Jun Li, 2010. "Identification of referencing and citation processes of scientific journals based on the citation distribution model," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 249-261, February.
    • Handle: RePEc:spr:scient:v:82:y:2010:i:2:d:10.1007_s11192-009-0085-z
    DOI: 10.1007/s11192-009-0085-z
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Guijie Zhang & Yuqiang Feng & Guang Yu & Luning Liu & Yanqiqi Hao, 2017. "Analyzing the time delay between scientific research and technology patents based on the citation distribution model," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1287-1306, June.
    2. Mingyang Wang & Shijia Jiao & Kah-Hin Chai & Guangsheng Chen, 2019. "Building journal’s long-term impact: using indicators detected from the sustained active articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 261-283, October.
    3. Hu, Zewen & Wu, Yishan, 2014. "Regularity in the time-dependent distribution of the percentage of never-cited papers: An empirical pilot study based on the six journals," Journal of Informetrics, Elsevier, vol. 8(1), pages 136-146.
    4. Lin Zhang & Wolfgang Glänzel, 2017. "A citation-based cross-disciplinary study on literature ageing: part II—diachronous aspects," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1559-1572, June.
    5. Finardi, Ugo, 2014. "On the time evolution of received citations, in different scientific fields: An empirical study," Journal of Informetrics, Elsevier, vol. 8(1), pages 13-24.
    6. Mingyang Wang & Jiaqi Zhang & Guangsheng Chen & Kah-Hin Chai, 2019. "Examining the influence of open access on journals’ citation obsolescence by modeling the actual citation process," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1621-1641, June.
    7. Yongli Li & Guijie Zhang & Yuqiang Feng & Chong Wu, 2015. "An entropy-based social network community detecting method and its application to scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 1003-1017, January.
    8. Hamid Bouabid, 2011. "Revisiting citation aging: a model for citation distribution and life-cycle prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 199-211, July.

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