Approaches to blockmodeling dynamic networks : a Monte Carlo simulation study

Cugmas, Marjan (avtor), Žiberna, Aleš (avtor)

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.

• Jezik: Angleški jezik
• Ključne besede: dynamic networks, stochastic blockmodeling, k-means blockmodeling, simulations, local mechanisms, evaluation
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FDV - Fakulteta za družbene vede
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2023
• Št. strani: Str. 7-19
• Številčenje: Vol. 73
• PID: 20.500.12556/RUL-143411
• UDK: 303
• ISSN pri članku: 0378-8733
• DOI: 10.1016/j.socnet.2022.12.003
• COBISS.SI-ID: 134684931
• Datum objave v RUL: 20.12.2022

CUGMAS, Marjan in ŽIBERNA, Aleš, 2023, Approaches to blockmodeling dynamic networks : a Monte Carlo simulation study. Social networks [na spletu]. 2023. Vol. 73, p. 7–19. [Dostopano 4 april 2025]. DOI 10.1016/j.socnet.2022.12.003. Pridobljeno s: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=slv&id=143411

Gradivo je del revije

• Naslov: Social networks
• Skrajšan naslov: Soc. networks
• Založnik: Elsevier
• ISSN: 0378-8733
• COBISS.SI-ID: 30632960

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: družbena omrežja, analiza omrežij, družbene vede, bločno modeliranje

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P5-0168
• Naslov: Družboslovna metodologija, statistika in informatika

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: J5-2557
• Naslov: Primerjava in evalvacija pristopov za bločno modeliranje časovnih omrežij s simulacijami in uporaba na slovenskih so-avtorskih omrežjih