FSS, J. Goričar Central Social Sciences Library, Ljubljana (ODKLJ)
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K-means-based algorithm for blockmodeling linked networksŽiberna, AlešThe 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.Source: Social Networks. - ISSN 0378-8733 (Vol. 61, May 2020, str. 153-169)Type of material - article, component partPublish date - 2020Language - englishCOBISS.SI-ID - 36567901
Author
Žiberna, Aleš
Topics
Analiza omrežij |
Network analysis |
Bločno modeliranje |
Blockmodeling |
Algoritmi |
Algorithms
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Žiberna, Aleš | 27576 |
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