izpis_h1_title_alt

k-means-based algorithm for blockmodeling linked networks
ID Žiberna, Aleš (Avtor)

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URLURL - Izvorni URL, za dostop obiščite https://www.sciencedirect.com/science/article/pii/S0378873319300176 Povezava se odpre v novem oknu

Izvleček
The paper presents a k-means-based algorithm for blockmodeling linked networks where linked networks are defined as a collection of one-mode and two-mode networks in which units from different one-mode networks are connected through two-mode networks. The reason for this is that a faster algorithm is needed for blockmodeling linked networks that can better scale to larger networks. Examples of linked networks include multilevel networks, dynamic networks, dynamic multilevel networks, and meta-networks. Generalized blockmodeling has been developed for linked/multilevel networks, yet the generalized blockmodeling approach is too slow for analyzing larger networks. Therefore, the flexibility of generalized blockmodeling is sacrificed for the speed of k-means-based approaches, thus allowing the analysis of larger networks. The presented algorithm is based on the two-mode k-means (or KL-means) algorithm for two-mode networks or matrices. As a side product, an algorithm for one-mode blockmodeling of one-mode networks is presented. The algorithm's use on a dynamic multilevel network with more than 400 units is presented. A situation study is also conducted which shows that k-means based algorithms are superior to relocation algorithm-based methods for larger networks (e.g. larger than 800 units) and never much worse.

Jezik:Angleški jezik
Ključne besede:generalised blockmodeling, k-means algorithm, homogeneity blockmodeling, linked networks, multilevel networks, simulations
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:2020
Št. strani:Str. 153-169
Številčenje:Vol. 61
PID:20.500.12556/RUL-128412 Povezava se odpre v novem oknu
UDK:303
ISSN pri članku:0378-8733
DOI:10.1016/j.socnet.2019.10.006 Povezava se odpre v novem oknu
COBISS.SI-ID:36567901 Povezava se odpre v novem oknu
Datum objave v RUL:12.07.2021
Število ogledov:812
Število prenosov:514
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Gradivo je del revije

Naslov:Social networks
Skrajšan naslov:Soc. networks
Založnik:Elsevier
ISSN:0378-8733
COBISS.SI-ID:30632960 Povezava se odpre v novem oknu

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.

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:J7-8279
Naslov:Bločno modeliranje večnivojskih in časovnih omrežij

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