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To account for strong aging characteristics of citation networks, we modifyGoogle's PageRank algorithm by initially distributing random surfersexponentially with age, in favor of more recent publications. The output ofthis algorithm, which we call CiteRank, is interpreted as approximate trafficto individual publications in a simple model of how researchers find newinformation. We develop an analytical understanding of traffic flow in terms ofan RPA-like model and optimize parameters of our algorithm to achieve the bestperformance. The results are compared for two rather different citationnetworks: all American Physical Society publications and the set of high-energyphysics theory (hep-th) preprints. Despite major differences between these twonetworks, we find that their optimal parameters for the CiteRank algorithm areremarkably similar.Comment: 4 pages, 3 figure

Ranking scientific publications using a model of network traffic