Determining Factors Behind the PageRank Log-Log Plot

We study the relation between PageRank and other parameters of information networks such as in-degree, out-degree, and the fraction of dangling nodes. We model this relation through a stochastic equation inspired by the original definition of PageRank. Further, we use the theory of regular variation...

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Bibliographic Details
Published inAlgorithms and Models for the Web-Graph pp. 108 - 123
Main Authors Volkovich, Yana, Litvak, Nelly, Donato, Debora
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
PageRank
Power laws
Ranking algorithms
Stochastic equations
Web graph
Wikipedia
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Summary:We study the relation between PageRank and other parameters of information networks such as in-degree, out-degree, and the fraction of dangling nodes. We model this relation through a stochastic equation inspired by the original definition of PageRank. Further, we use the theory of regular variation to prove that PageRank and in-degree follow power laws with the same exponent. The difference between these two power laws is in a multiplicative constant, which depends mainly on the fraction of dangling nodes, average in-degree, the power law exponent, and the damping factor. The out-degree distribution has a minor effect, which we explicitly quantify. Finally, we propose a ranking scheme which does not depend on out-degrees.
ISBN:9783540770039
3540770038
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-77004-6_9