20.500.12556/RUL-128412 k-means-based algorithm for blockmodeling linked networks 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. generalised blockmodeling k-means algorithm homogeneity blockmodeling linked networks multilevel networks simulations true false true Angleški jezik Ni določen Članek v reviji 2021-07-12 09:11:51 2021-07-12 09:11:56 2022-09-07 04:15:01 0000-00-00 00:00:00 2020 0 0 Str. 153-169 Vol. 61 May 2020 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 303 0378-8733 10.1016/j.socnet.2019.10.006 36567901 RAZ_Ziberna_Ales_2020.pdf RAZ_Ziberna_Ales_2020.pdf 1 1DDAAD2C7E0DF5440B75CECF636CF49A 9f5d2ffaf1a674fc42aa88b9a1e39c607e7379de791e54799684c235b5ccb9bd 1113fe76-e2e6-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=145145 https://www.sciencedirect.com/science/article/pii/S0378873319300176 1 4d46ddf8-e2e0-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=145138 Fakulteta za družbene vede 0 0 0