Around power law for PageRank components in Buckley-Osthus model of web graph
Alexander Gasnikov, Maxim Zhukovskii, Sergey Kim, Fedor Noskov, Stepan, Plaunov, Daniil Smirnov
TL;DR
This paper investigates the power law distribution of PageRank components in the Buckley-Osthus web graph model, comparing numerical methods and confirming the power law hypothesis through extensive experiments.
Contribution
It introduces a comprehensive comparison of numerical methods for PageRank calculation within the Buckley-Osthus model and confirms the power law distribution of PageRank components.
Findings
Power law distribution confirmed for PageRank components
Best numerical method identified for PageRank computation
Numerical experiments support the power law hypothesis
Abstract
In the paper we investigate power law for PageRank components for the Buckley-Osthus model for web graph. We compare different numerical methods for PageRank calculation. With the best method we do a lot of numerical experiments. These experiments confirm the hypothesis about power law. At the end we discuss real model of web-ranking based on the classical PageRank approach.
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Game Theory and Applications