Abstract
In Chap. 4 we presented the calibration procedure, namely, the measurements of the empirical functions and parameters of the model. These measurements were focused on the deterministic component of citation dynamics while the stochastic component was averaged out. Here, we focus on the fluctuating component of citation dynamics of individual papers and verify that it is captured by the model as well.
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References
Burrell, Q. L. (2013). A stochastic approach to the relation between the impact factor and the uncitedness factor. Journal of Informetrics, 7(3), 676–682.
Gao, J., Barzel, B., & Barabási, A. L. (2016). Universal resilience patterns in complex networks. Nature, 530, 307.
Golosovsky, M. (2017). Power-law citation distributions are not scale-free. Physical Review E, 96(3), 032306.
Golosovsky, M., & Solomon, S. (2012). Stochastic dynamical model of a growing citation network based on a self-exciting point process. Physical Review Letters, 109(9), 098701.
Golosovsky, M., & Solomon, S. (2017). Growing complex network of citations of scientific papers: Modeling and measurements. Physical Review E, 95(1), 012324.
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Golosovsky, M. (2019). Model Validation. In: Citation Analysis and Dynamics of Citation Networks. SpringerBriefs in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-28169-4_5
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DOI: https://doi.org/10.1007/978-3-030-28169-4_5
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