Related Research Articles
Vladimir Batagelj is a Slovenian mathematician and an emeritus professor of mathematics at the University of Ljubljana. He is known for his work in discrete mathematics and combinatorial optimization, particularly analysis of social networks and other large networks (blockmodeling).
Harrison Colyar White was an American sociologist who was the Giddings Professor of Sociology at Columbia University. White played an influential role in the “Harvard Revolution” in social networks and the New York School of relational sociology. He is credited with the development of a number of mathematical models of social structure including vacancy chains and blockmodels. He has been a leader of a revolution in sociology that is still in process, using models of social structure that are based on patterns of relations instead of the attributes and attitudes of individuals.
Mathematical sociology is an interdisciplinary field of research concerned with the use of mathematics within sociological research.
Thomas J. Fararo was Distinguished Service Professor Emeritus at the University of Pittsburgh. After earning a Ph.D. in sociology at Syracuse University in 1963, he received a three-year postdoctoral fellowship for studies in pure and applied mathematics at Stanford University (1964–1967). In 1967, he joined the faculty of University of Pittsburgh; during 1972-1973, he was visiting professor at the University of York in England.
Tom A. B. Snijders is professor of Statistics in the Social Sciences at Nuffield College, Oxford, one of the constituent colleges of the University of Oxford. He is also professor of Methodology at the University of Groningen, a position he has held for more than twenty years.
Social network analysis (SNA) software is software which facilitates quantitative or qualitative analysis of social networks, by describing features of a network either through numerical or visual representation.
Anuška Ferligoj is a Slovenian mathematician, born August 19, 1947, in Ljubljana, Slovenia, whose specialty is statistics and network analysis. Her specific interests include multivariate analysis, cluster analysis, social network analysis, methodological research of public opinion, analysis of scientific networks. She is a professor emeritus at the University of Ljubljana, Slovenia.
Main path analysis is a mathematical tool, first proposed by Hummon and Doreian in 1989, to identify the major paths in a citation network, which is one form of a directed acyclic graph (DAG). It has since become an effective technique for mapping technological trajectories, exploring scientific knowledge flows, and conducting literature reviews.
Blockmodeling is a set or a coherent framework, that is used for analyzing social structure and also for setting procedure(s) for partitioning (clustering) social network's units, based on specific patterns, which form a distinctive structure through interconnectivity. It is primarily used in statistics, machine learning and network science.
Aleš Žiberna is a Slovene statistician, whose specialty is network analysis. His specific research interests include blockmodeling, multivariate analysis and computer intensive methods.
In generalized blockmodeling, the blockmodeling is done by "the translation of an equivalence type into a set of permitted block types", which differs from the conventional blockmodeling, which is using the indirect approach. It's a special instance of the direct blockmodeling approach.
Andrej Mrvar is a Slovenian computer scientist and a professor at the University of Ljubljana. He is known for his work in network analysis, graph drawing, decision making, virtual reality, electronic timing and data processing of sports competitions.
Deterministic blockmodeling is an approach in blockmodeling that does not assume a probabilistic model, and instead relies on the exact or approximate algorithms, which are used to find blockmodel(s). This approach typically minimizes some inconsistency that can occur with the ideal block structure. Such analysis is focused on clustering (grouping) of the network that is obtained with minimizing an objective function, which measures discrepancy from the ideal block structure.
In mathematics applied to analysis of social structures, homogeneity blockmodeling is an approach in blockmodeling, which is best suited for a preliminary or main approach to valued networks, when a prior knowledge about these networks is not available. This is due to the fact, that homogeneity blockmodeling emphasizes the similarity of link (tie) strengths within the blocks over the pattern of links. In this approach, tie (link) values are assumed to be equal (homogenous) within blocks.
Blockmodeling linked networks is an approach in blockmodeling in analysing the linked networks. Such approach is based on the generalized multilevel blockmodeling approach. The main objective of this approach is to achieve clustering of the nodes from all involved sets, while at the same time using all available information. At the same time, all one-mode and two-node networks, that are connected, are blockmodeled, which results in obtaining only one clustering, using nodes from each sets. Each cluster ideally contains only nodes from one set, which also allows the modeling of the links among clusters from different sets. This approach was introduced by Aleš Žiberna in 2014.
Linked network in statistics is a network, which is composed of one-node networks, where the nodes from different one-node networks are connected through two-node networks. This means, that "linked networks are collections of networks defined on different sets of nodes", where all sets of nodes must be connected to each other.
Exploratory blockmodeling is an (inductive) approach in blockmodeling regarding the specification of an ideal blockmodel. This approach, also known as hypotheses-generating, is the simplest approach, as it "merely involves the definition of the block types permitted as well as of the number of clusters." With this approach, researcher usually defines the best possible blockmodel, which then represent the base for the analysis of the whole network.
Confirmatory blockmodeling is a deductive approach in blockmodeling, where a blockmodel is prespecify before the analysis, and then the analysis is fit to this model. When only a part of analysis is prespecify, it is called partially confirmatory blockmodeling.
Implicit blockmodeling is an approach in blockmodeling, similar to a valued and homogeneity blockmodeling, where initially an additional normalization is used and then while specifying the parameter of the relevant link is replaced by the block maximum.
Generalized blockmodeling of binary networks is an approach of generalized blockmodeling, analysing the binary network(s).
References
- ↑ Patrickdoreian.com - About Me
- ↑ FDV.uni-lj.si - Professor Patrick Doreian from the University of Pittsburgh
- ↑ Doreian, Patrick; Batagelj, Vladimir; Ferligoj, Anuška (2005). Generalized Blackmodeling. Cambridge University Press. ISBN 0-521-84085-6.
- ↑ Fararo, Thomas J; Doreian, Patrick (1984). "Tripartite structural analysis". Social Networks. 6 (2): 141–175. doi:10.1016/0378-8733(84)90015-7.
- ↑ Hummon, Norman P.; Doreian, Patrick (1989). "Connectivity in a citation network: The development of DNA theory". Social Networks. 11 (1): 39–63. doi:10.1016/0378-8733(89)90017-8.
- ↑ Žiberna, Aleš (2009). "Evaluation of Direct and Indirect Blockmodeling of Regular Equivalence in Valued Networks by Simulations". Metodološki zvezki. 6 (2): 99–134.
- ↑ "The Section on Mathematical Sociology's Harrison White Outstanding Book Award". American Sociological Association. 4 October 2011. Retrieved September 26, 2019.
