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).
Addressing modes are an aspect of the instruction set architecture in most central processing unit (CPU) designs. The various addressing modes that are defined in a given instruction set architecture define how the machine language instructions in that architecture identify the operand(s) of each instruction. An addressing mode specifies how to calculate the effective memory address of an operand by using information held in registers and/or constants contained within a machine instruction or elsewhere.
Mathematical sociology is the area of sociology that uses mathematics to construct social theories. Mathematical sociology aims to take sociological theory and to express it in mathematical terms. The benefits of this approach include increased clarity and the ability to use mathematics to derive implications of a theory that cannot be arrived at intuitively. In mathematical sociology, the preferred style is encapsulated in the phrase "constructing a mathematical model." This means making specified assumptions about some social phenomenon, expressing them in formal mathematics, and providing an empirical interpretation for the ideas. It also means deducing properties of the model and comparing these with relevant empirical data. Social network analysis is the best-known contribution of this subfield to sociology as a whole and to the scientific community at large. The models typically used in mathematical sociology allow sociologists to understand how predictable local interactions are and they are often able to elicit global patterns of social structure.
Social network analysis 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 Fellow of the European Academy of Sociology.
Similarity in network analysis occurs when two nodes fall in the same equivalence class.
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.
Blockmodel in blockmodeling is defined as a multitude of structures, which are obtained with:
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.
Patrick Doreian is an American mathematician and social scientist, whose specialty is network analysis. His specific research interests include blockmodeling, social structure and network processeses.
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 approach in blockmodeling, that does not assume probabilistic model, and instead relies on the exact or approximate algorithms, which are used to find blockmodel(s). This approach typical minimizes some inconsistency, that can accure 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.
Generalized blockmodeling of valued networks is an approach of the generalized blockmodeling, dealing with valued networks.
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 anaylsis 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.
Generalized blockmodeling of binary networks is an approach of generalized blockmodeling, analysing the binary network(s).
