Parameter estimators of sparse random intersection graphs with thinned communities

Joona Karjalainen, Johan S.H. van Leeuwaarden, Lasse Leskelä

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

    2 Citations (Scopus)


    This paper studies a statistical network model generated by a large number of randomly sized overlapping communities, where any pair of nodes sharing a community is linked with probability q via the community. In the special case with q= 1 the model reduces to a random intersection graph which is known to generate high levels of transitivity also in the sparse context. The parameter q adds a degree of freedom and leads to a parsimonious and analytically tractable network model with tunable density, transitivity, and degree fluctuations. We prove that the parameters of this model can be consistently estimated in the large and sparse limiting regime using moment estimators based on partially observed densities of links, 2-stars, and triangles.

    Original languageEnglish
    Title of host publicationAlgorithms and Models for the Web Graphs
    Subtitle of host publication15th International Workshop, WAW 2018, Moscow, Russia, May 17-18, 2018, Proceedings
    EditorsA. Bonato, P. Pralat, A, Raigorodskii
    Place of PublicationDordrecht
    Number of pages15
    ISBN (Electronic)978-3-319-92871-5
    ISBN (Print)978-3-319-92870-8
    Publication statusPublished - 1 Jan 2018
    Event15th Workshop on Algorithms and Models for the Web Graph, WAW 2018 - Moscow, Russian Federation
    Duration: 17 May 201818 May 2018

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume10836 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference15th Workshop on Algorithms and Models for the Web Graph, WAW 2018
    CountryRussian Federation

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