Approaches to blockmodeling dynamic networks : a Monte Carlo simulation study

Cugmas, Marjan (author), Žiberna, Aleš (author)

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.

• Language: English
• Keywords: dynamic networks, stochastic blockmodeling, k-means blockmodeling, simulations, local mechanisms, evaluation
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FDV - Faculty of Social Sciences
• Publication status: Published
• Publication version: Version of Record
• Year: 2023
• Number of pages: Str. 7-19
• Numbering: Vol. 73
• PID: 20.500.12556/RUL-143411
• UDC: 303
• ISSN on article: 0378-8733
• DOI: 10.1016/j.socnet.2022.12.003
• COBISS.SI-ID: 134684931
• Publication date in RUL: 20.12.2022

Record is a part of a journal

• Title: Social networks
• Shortened title: Soc. networks
• Publisher: Elsevier
• ISSN: 0378-8733
• COBISS.SI-ID: 30632960

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: družbena omrežja, analiza omrežij, družbene vede, bločno modeliranje

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: P5-0168
• Name: Družboslovna metodologija, statistika in informatika

• Funder: ARRS - Slovenian Research Agency
• Project number: J5-2557
• Name: Primerjava in evalvacija pristopov za bločno modeliranje časovnih omrežij s simulacijami in uporaba na slovenskih so-avtorskih omrežjih