Ranking scientific publications using a model of network traffic

Dylan Walker, Huafeng Xie, Koon Kiu Yan, Sergei Maslov

Research output: Contribution to journalArticlepeer-review


To account for strong ageing characteristics of citation networks, we modify the PageRank algorithm by initially distributing random surfers exponentially with age, in favour of more recent publications. The output of this algorithm, which we call CiteRank, is interpreted as approximate traffic to individual publications in a simple model of how researchers find new information. We optimize parameters of our algorithm to achieve the best performance. The results are compared for two rather different citation networks: all American Physical Society publications between 1893 and 2003 and the set of high-energy physics theory (hep-th) preprints. Despite major differences between these two networks, we find that their optimal parameters for the CiteRank algorithm are remarkably similar. The advantages and performance of CiteRank over more conventional methods of ranking publications are discussed.

Original languageEnglish (US)
Article numberP06010
JournalJournal of Statistical Mechanics: Theory and Experiment
Issue number6
StatePublished - Jun 1 2007
Externally publishedYes


  • Communication
  • Network dynamics
  • New applications of statistical mechanics
  • Supply and information networks

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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