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Ranking scientific publications using a model of network traffic

Dylan Walker et al J. Stat. Mech. (2007) P06010   doi: 10.1088/1742-5468/2007/06/P06010  Help

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Dylan Walker1,2, Huafeng Xie2,3, Koon-Kiu Yan1,2 and Sergei Maslov2
1 Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794, USA
2 Department of Condensed Matter Physics and Materials Science, Brookhaven National Laboratory, Upton, NY 11973, USA
3 New Media Lab, The Graduate Center, CUNY, New York, NY 10016, USA
E-mail: dwalker@grad.physics.sunysb.edu, hxie@bnl.gov, kyan@bnl.gov and maslov@bnl.gov

Abstract. 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.

Key words: network dynamics; new applications of statistical mechanics; communication, supply and information networks

E-print number: physics/0612122
Cited: by
Refers: to

Received 27 December 2006, accepted for publication 24 May 2007
Published 14 June 2007

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