Blockmodeling: Difference between revisions

Revision as of 09:27, 18 August 2021

Revision as of 09:28, 18 August 2021

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== Different approaches ==

Regarding what kind of network is being blockmodeled, different approach is necessary. Networks can be one-modeone–mode or two-modetwo–mode. In former all units can be connected to any other unit and where units are of the same type, while in latter the units are connected only to the unit(s) of a different type.<ref name="gener-blackgener–black"/>{{rp|6–10}} Regarding relationships between units, they can be single-relationalsingle–relational or multi-relationalmulti–relational networks. Further more, the networks can be temporal or multileveland also binary (only 0 and 1) or signed (allowing negative ties)/values (other values are possible) networks.

Different approaches to blockmodeling can be grouped into two main classes: [[deterministic blockmodeling]] and [[stochastic blockmodeling]] approaches. Deterministic blockmodeling is then further divided into direct and indirect blockmodeling approaches.<ref name="ReferenceA"/>

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According to Brusco and Steinley (2011),<ref>{{cite journal |last1=Brusco |first1=Michael |last2=Steinley |first2=Douglas|date=2011 |title=A tabu search heuristic for deterministic two-mode blockmodeling |url= |journal=Psychometrika |volume=76 |issue= |pages=612-633 |doi= |access-date=}}</ref> the blockmodeling can be categorized (using a number of dimensions):<ref>{{cite journal |last1=Brusco |first1=Michael |last2=Doreian |first2=Patrick |last3=Steinley |first3=Douglas |last4=Satornino |first4=Cinthia B. |date=2013 |title=Multiobjective blockmodeling for social network analysis |url= |journal=Psychometrika |volume=78 |issue=3 |pages=498-525 |doi= 10.1007/S11336-012-9313-1 |access-date=}}</ref>

* [[deterministic blockmodeling|deterministic]] or [[stochastic blockmodeling]],

* [[one-modeone–mode network|one-modeone–mode]] or [[two-modetwo–mode network]]s,

* [[signed network|signed]] or [[unsigned network]]s,

* [[exploratory blockmodeling|exploratory]] or [[confirmatory blockmodeling]].

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== Specialized programs ==

Blockmodeling is done with specialized [[computer program]]s, dedicated to the analysis of a large networks, as:

* '''BLOCKS''',<ref name="stats.ox.ac.uk">[https://www.stats.ox.ac.uk/~snijders/socnet.htm STATS.ox.ac.uk -– Social Network Analysis]</ref>

* '''[[CONCOR]]''',<ref>{{cite journal |last1=Steiber |first1=Steven R. |date=1981 |title=Building better blockmodels: A non-hierarchicalnon–hierarchical extension of CONCOR with applications to regression analysis |url= |journal=Mid-AmericanMid–American Review of Sociology |volume=VI |issue= |pages=17-4017–40 |doi=}}</ref>

* '''Model''' ([[Vladimir Batagelj]]),<ref name="Generalized Blockmodeling with Paje">{{cite journal |last1=Batagelj |first1=Vladimir |last2=Mrvar |first2=andrej |last3=Ferligoj |first3=Anuška |last4=Doreian |first4=Patrick |date=2004 |title=Generalized Blockmodeling with Pajek |url= |journal=Metodološki zvezki |volume=1 |issue=2 |pages=455–467 |doi=}}</ref>

* '''Model2''' (Vladimir Batagelj),<ref name="Generalized Blockmodeling with Paje"/>

* '''[[Pajek]]''' (Vladimir Batagelj and [[Andrej Mrvar]]),<ref name="Generalized Blockmodeling with Paje"/>

* '''R–package Blockmodeling''' ([[Aleš Žiberna]]),...<ref name="Absent Ties in Social Networks, the"/><ref>[https://cran.r–project.org/web/packages/blockmodeling/blockmodeling.pdf Cran.R–project.org – Package 'blockmodeling']</ref><ref name="ReferenceA"/>

* '''SIENA''',<ref>[https://www. name="stats.ox.ac.uk"/~snijders/socnet.htm STATS.ox.ac.uk - Social Network Analysis</ref>

* '''SNOWBALL''',<ref>[https://www. name="stats.ox.ac.uk"/~snijders/socnet.htm STATS.ox.ac.uk - Social Network Analysis</ref>

* '''StOCNET''',<ref>[https://www. name="stats.ox.ac.uk"/~snijders/socnet.htm STATS.ox.ac.uk - Social Network Analysis</ref>

* '''ZO''',<ref>[https://www. name="stats.ox.ac.uk"/~snijders/socnet.htm STATS.ox.ac.uk - Social Network Analysis</ref>

== See also ==

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{{Social networking}}

[[Category:Machine learning]]

[[Category:Network science]]