 | This article provides insufficient context for those unfamiliar with the subject. (September 2021) |
Generalized blockmodeling of binary networks (also relational blockmodeling) is an approach of generalized blockmodeling, analysing the binary network(s). [1]
As most network analyses deal with binary networks, this approach is also considered as the fundamental approach of blockmodeling. [2]: 11 This is especially noted, as the set of ideal blocks, when used for interpretation of blockmodels, have binary link patterns, which precludes them to be compared with valued empirical blocks. [3]
When analysing the binary networks, the criterion function is measuring block inconsistencies, while also reporting the possible errors. [1] The ideal block in binary blockmodeling has only three types of conditions: "a certain cell must be (at least) 1, a certain cell must be 0 and the over each row (or column) must be at least 1". [1]
It is also used as a basis for developing the generalized blockmodeling of valued networks. [1]
- ^ a b c d Žiberna, Aleš (2007). "Generalized Blockmodeling of Valued Networks". Social Networks. 29: 105–126. arXiv: 1312.0646. doi: 10.1016/j.socnet.2006.04.002. S2CID 17739746.
- ^ Doreian, Patrick; Batagelj, Vladimir; Ferligoj, Anuška (2005). Generalized Blackmodeling. Cambridge University Press. ISBN 0-521-84085-6.
- ^ Nordlund, Carl (2016). "A deviational approach to blockmodeling of valued networks". Social Networks. 44: 160–178. doi: 10.1016/j.socnet.2015.08.004.
| This article provides insufficient context for those unfamiliar with the subject. (September 2021) |
Generalized blockmodeling of binary networks (also relational blockmodeling) is an approach of generalized blockmodeling, analysing the binary network(s). [1]
As most network analyses deal with binary networks, this approach is also considered as the fundamental approach of blockmodeling. [2]: 11 This is especially noted, as the set of ideal blocks, when used for interpretation of blockmodels, have binary link patterns, which precludes them to be compared with valued empirical blocks. [3]
When analysing the binary networks, the criterion function is measuring block inconsistencies, while also reporting the possible errors. [1] The ideal block in binary blockmodeling has only three types of conditions: "a certain cell must be (at least) 1, a certain cell must be 0 and the over each row (or column) must be at least 1". [1]
It is also used as a basis for developing the generalized blockmodeling of valued networks. [1]
- ^ a b c d Žiberna, Aleš (2007). "Generalized Blockmodeling of Valued Networks". Social Networks. 29: 105–126. arXiv: 1312.0646. doi: 10.1016/j.socnet.2006.04.002. S2CID 17739746.
- ^ Doreian, Patrick; Batagelj, Vladimir; Ferligoj, Anuška (2005). Generalized Blackmodeling. Cambridge University Press. ISBN 0-521-84085-6.
- ^ Nordlund, Carl (2016). "A deviational approach to blockmodeling of valued networks". Social Networks. 44: 160–178. doi: 10.1016/j.socnet.2015.08.004.