Assortativity and bidegree distributions on Bernoulli random graph superpositions

Mindaugas Bloznelis, Joona Karjalainen, Lasse Leskelä*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1 Citation (Scopus)


A probabilistic generative network model with n nodes and m overlapping layers is obtained as a superposition of m mutually independent Bernoulli random graphs of varying size and strength. When n and m are large and of the same order of magnitude, the model admits a sparse limiting regime with a tunable power-law degree distribution and nonvanishing clustering coefficient. This article presents an asymptotic formula for the joint degree distribution of adjacent nodes. This yields a simple analytical formula for the model assortativity, and opens up ways to analyze rank correlation coefficients suitable for random graphs with heavy-tailed degree distributions.
Original languageEnglish
Title of host publicationAlgorithms and Models for the Web Graph - 17th International Workshop, WAW 2020, Proceedings
Subtitle of host publication17th International Workshop, WAW 2020, Warsaw, Poland, September 21–22, 2020, Proceedings
EditorsBogumil Kaminski, Przemyslaw Szufel, Pawel Pralat
Number of pages14
ISBN (Electronic)978-3-030-48478-1
Publication statusPublished - 2 Jun 2020
MoE publication typeA4 Article in a conference publication
EventWorkshop on Algorithms and Models for the Web Graph - SGH Warsaw School of Economics, Warsaw, Poland
Duration: 21 Sep 202022 Sep 2020
Conference number: 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


WorkshopWorkshop on Algorithms and Models for the Web Graph
Abbreviated titleWAW
Internet address


  • Joint degree distribution
  • Bidegree distribution
  • Degree–degree distribution
  • Empirical degree distribution
  • Degree correlation
  • Transitivity
  • Statistical network model
  • Erdős–Rényi graph
  • Random intersection graph


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