Characterizing and modeling citation dynamics

Young-Ho Eom, Santo Fortunato

Research output: Contribution to journalArticle

95 Citations (Scopus)

Abstract

Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.
LanguageEnglish
Article numbere24926
Pages1-7
Number of pages7
JournalPLoS One
Volume6
Issue number9
DOIs
Publication statusPublished - 22 Sep 2011

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Citations
Bibliometrics
Modeling
Publications
Burst
statistics
Statistics
Power Law
Kolmogorov-Smirnov Statistic
Preferential Attachment
Goodness of fit
bibliometric analysis

Keywords

  • citation dynamics
  • citation distribution
  • bibliometric data

Cite this

Eom, Young-Ho ; Fortunato, Santo. / Characterizing and modeling citation dynamics. In: PLoS One. 2011 ; Vol. 6, No. 9. pp. 1-7.
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Characterizing and modeling citation dynamics. / Eom, Young-Ho; Fortunato, Santo.

In: PLoS One, Vol. 6, No. 9, e24926, 22.09.2011, p. 1-7.

Research output: Contribution to journalArticle

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