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Ranking scientific publications using a model of network traffic

Dylan Walker1,2, Huafeng Xie2,3, Koon-Kiu Yan1,2 and Sergei Maslov2

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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.


Keywords

new applications of statistical mechanics

network dynamics

communication, supply and information networks

 

E-print Number: physics/0612122

Cited: by |

Refers: to

PACS

89.20.Hh World Wide Web, Internet

84.40.Ua Telecommunications: signal transmission and processing; communication satellites

MSC

68Wxx Algorithms (For numerical algorithms, see 65-XX; for combinatorics and graph theory, see 68Rxx)

68M10 Network design and communication (See also 68R10, 90B18)

Subjects

Electronics and devices

Dates

Issue 06 (June 2007)

Received 27 December 2006, accepted for publication 24 May 2007

Published 14 June 2007



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