Empirical Validation of the Buckley--Osthus Model for the Web Host Graph: Degree and Edge Distributions
Maxim Zhukovskiy, Dmitry Vinogradov, Yuri Pritykin, Liudmila, Ostroumova, Evgeniy Grechnikov, Gleb Gusev, Pavel Serdyukov and, Andrei Raigorodskii

TL;DR
This study empirically validates that the Buckley--Osthus preferential attachment model accurately captures both degree and edge distributions of the web host graph, demonstrating its effectiveness over other models.
Contribution
It is the first to show that a single parameter of the Buckley--Osthus model fits both degree and edge distributions of real web graphs.
Findings
The model's parameter $a$ fits both degree and edge distributions independently.
The Buckley--Osthus model accurately reflects the asymptotic edge distribution of the web host graph.
Other models fail to replicate the edge distribution despite matching degree distribution.
Abstract
There has been a lot of research on random graph models for large real-world networks such as those formed by hyperlinks between web pages in the world wide web. Though largely successful qualitatively in capturing their key properties, such models may lack important quantitative characteristics of Internet graphs. While preferential attachment random graph models were shown to be capable of reflecting the degree distribution of the webgraph, their ability to reflect certain aspects of the edge distribution was not yet well studied. In this paper, we consider the Buckley--Osthus implementation of preferential attachment and its ability to model the web host graph in two aspects. One is the degree distribution that we observe to follow the power law, as often being the case for real-world graphs. Another one is the two-dimensional edge distribution, the number of edges between vertices…
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence
