VSE knjižnice (vzajemna bibliografsko-kataložna baza podatkov COBIB.SI)
  • Approaches to blockmodeling dynamic networks : a Monte Carlo simulation study
    Cugmas, Marjan ; Žiberna, Aleš
    Blockmodeling refers to a variety of statistical methods for reducing and simplifying large and complex networks. While methods for blockmodeling networks observed at one time point are well ... established, it is only recently that researchers have proposed several methods for analysing dynamic networks (i.e., networks observed at multiple time points). The considered approaches are based on k-means or stochastic blockmodeling, with different ways being used to model time dependency among time points. Their novelty means they have yet to be extensively compared and evaluated and the paper therefore aims to compare and evaluate them using Monte Carlo simulations. Different network characteristics are considered, including whether tie formation is random or governed by local network mechanisms. The results show the Dynamic Stochastic Blockmodel (Matias and Miele 2017) performs best if the blockmodel does not change; otherwise, the Stochastic Blockmodel for Multipartite Networks (Bar-Hen et al. 2020) does.
    Vir: Social Networks. - ISSN 0378-8733 (Vol. 73, May 2023, str. 7-19)
    Vrsta gradiva - članek, sestavni del
    Leto - 2023
    Jezik - angleški
    COBISS.SI-ID - 134684931

    Povezava(-e):

    Repozitorij Univerze v Ljubljani – RUL
    DOI

vir: Social Networks. - ISSN 0378-8733 (Vol. 73, May 2023, str. 7-19)
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