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Generalized preferential attachment considering aging

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  • Wu, Yan
  • Fu, Tom Z.J.
  • Chiu, Dah Ming

Abstract

Preferential Attachment (PA) models the scientific citation process. In the PA model, a new paper attaches itself to the citation network based only on the popularity of the currently existing papers. This invariably leads to a network whose degree distribution satisfies the Power Law. Yet, empirical results show that paper age should also play a role in the citation process. In other words, when references are chosen for a new paper, the age of an existing paper may also affect the choice for citing. In this paper, we derive a generalized PA model that includes the effect of aging, with analytical solution. Such a model can be used to analyze the competing influence of preferential attachment and aging effect quantitatively in citation process and explain differences in various research domains by the extent of aging. It may also serve as a general model of network formation.

Suggested Citation

  • Wu, Yan & Fu, Tom Z.J. & Chiu, Dah Ming, 2014. "Generalized preferential attachment considering aging," Journal of Informetrics, Elsevier, vol. 8(3), pages 650-658.
    • Handle: RePEc:eee:infome:v:8:y:2014:i:3:p:650-658
    DOI: 10.1016/j.joi.2014.06.002
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    References listed on IDEAS

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    Cited by:

    1. Thelwall, Mike, 2016. "Citation count distributions for large monodisciplinary journals," Journal of Informetrics, Elsevier, vol. 10(3), pages 863-874.
    2. S. R. Goldberg & H. Anthony & T. S. Evans, 2015. "Modelling citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1577-1604, December.
    3. Diego Raphael Amancio, 2015. "Comparing the topological properties of real and artificially generated scientific manuscripts," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1763-1779, December.
    4. Li, Bo & Sun, Duoyong & Bai, Guanghan, 2017. "Empirical research on evolutionary behavior of covert network with preference measurement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 33-43.
    5. Yi Bu & Tian-yi Liu & Win-bin Huang, 2016. "MACA: a modified author co-citation analysis method combined with general descriptive metadata of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 143-166, July.
    6. Clough, James R. & Evans, Tim S., 2016. "What is the dimension of citation space?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 235-247.

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