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Implicit 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. This approach was first proposed by Batagelj and Ferligoj in 2000, and developed by Aleš Žiberna Aleš Žiberna is a Slovene statistician, whose specialty is network analysis. His specific research interests include blockmodeling, multivariate analysis and computer intensive methods (e.g., computer simulations, resampling methods). Cur ... in 2007/08. Comparing with homogeneity, the implicit blockmodeling will perform similarly with max-regular equivalence, but slightly worse in other settings. It will perform worse than valued and homogeneity blockmodeling with a pre-specified blockmodel. References {{reflist See also * prespecific blockmodeling Blockmodeling ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Blockmodeling
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 ( nodes, vertices, actors), based on specific patterns, which form a distinctive structure through interconnectivity. Patrick Doreian, An Intuitive Introduction to Blockmodeling with Examples, ''BMS: Bulletin of Sociological Methodology'' / ''Bulletin de Méthodologie Sociologique'', January, 1999, No. 61 (January, 1999), pp. 5–34. It is primarily used in statistics, machine learning and network science. As an empirical procedure, blockmodeling assumes that all the units in a specific network can be grouped together to such extent to which they are equivalent. Regarding equivalency, it can be structural, regular or generalized. Anuška Ferligoj: Blockmodeling, http://mrvar.fdv.uni-lj.si/sola/info4/nusa/doc/blockmodeling-2.pdf Using blockmodeling, a network can be analyzed using newly created block ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Valued Blockmodeling
Generalized blockmodeling of valued networks is an approach of the generalized blockmodeling, dealing with valued networks (e.g., non–binary). While the generalized blockmodeling signifies a "formal and integrated approach for the study of the underlying functional anatomies of virtually any set of relational data", it is in principle used for binary networks. This is evident from the set of ideal blocks, which are used to interpret blockmodels, that are binary, based on the characteristic link patterns. Because of this, such templates are "not readily comparable with valued empirical blocks". To allow generalized blockmodeling of valued directional ( one–mode) networks (e.g. allowing the direct comparisons of empirical valued blocks with ideal binary blocks), a non–parametric approach is used. With this, "an optional parameter determines the prominence of valued ties as a minimum percentile deviation between observed and expected flows". Such two–sided application of param ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homogeneity Blockmodeling
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 (or statistical data computed on them) are assumed to be equal (homogenous) within blocks. This approach to the generalized blockmodeling of valued networks was first proposed by Aleš Žiberna in 2007 with the basic idea, "that the inconsistency of an empirical block with its ideal block can be measured by within block variability of appropriate values". The newly–formed ideal blocks, which are appropriate for blockmodeling of valued networks, are then presented together with the definitions of their block inconsistencies. Similar approach to t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Normalization (statistics)
In statistics and applications of statistics, normalization can have a range of meanings. In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging. In more complicated cases, normalization may refer to more sophisticated adjustments where the intention is to bring the entire probability distributions of adjusted values into alignment. In the case of normalization of scores in educational assessment, there may be an intention to align distributions to a normal distribution. A different approach to normalization of probability distributions is quantile normalization, where the quantiles of the different measures are brought into alignment. In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these normalized values allow the comparison of corresponding normalized values for different datasets i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Blockmodel
Blockmodel (sometimes also block model) in blockmodeling (part of network science) is defined as a multitude of structures, which are obtained with: * identification of all vertices (e.g., units, nodes) within a cluster and at the same time representing each cluster as a vertex, from which vertices for another graph can be constructed; * combination of all the links (ties), represented in a block as a single link between positions, while at the same time constructing one tie for each block. In a case, when there are no ties in a block, there will be no ties between the two positions, that define the block. In principle, blockmodeling, as a process, is composed from three steps. In the first step, the number of units is determined. This is followed (in the second step) by selection or determination of permitted blocks, that will occur and perhaps also the locations in the matrix. The last, third step, using computer program, the partitioning of units is done, according to the pre- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Vladimir Batagelj
Vladimir Batagelj (born June 14, 1948 in Idrija, Yugoslavia) 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). Education and career Vladimir Batagelj completed his Ph.D. at the University of Ljubljana in 1986 under the direction of Tomaž Pisanski. He stayed at the University of Ljubljana as a professor until his retirement, where he was a professor of sociology and statistics, while also being a chair of the Department of Sociology of the Faculty of Social Sciences. As visiting professor, he was taught at the University of Pittsburgh (1990-91) and at the University of Konstanz (2002). He was also a member of editorial boards of two journals: ''Informatica'' and ''Journal of Social Structure''. His work has been cited over 11000 times. His book ''Exploratory Social ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Anuška Ferligoj
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 (theory and application in social sciences, medicine, etc.), cluster analysis (constraints, multi-criteria clustering), social network analysis (blockmodeling, reliability and validity of network measurement), methodological research of public opinion, analysis of scientific networks. She is Fellow of the European Academy of Sociology. She is a Professor Emeritus (2020) at the University of Ljubljana, Slovenia, and has been employed by the Faculty of Social Sciences since 1972. In the 2003—2005, she was the dean of the Faculty of Social Sciences. In 1992 – 2012, she was the head of the Centre for Methodology and Informatics at the Institute of Social Sciences (currently – its associate member). In 2002 – 2013, she headed the Graduate Program on Statistics, and in 2012 – 202 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Aleš Žiberna
Aleš Žiberna is a Slovene statistician, whose specialty is network analysis. His specific research interests include blockmodeling, multivariate analysis and computer intensive methods (e.g., computer simulations, resampling methods). Currently, he is employed at the Faculty of Social Sciences of the University of Ljubljana, specifically at the Chair of Social Informatics and Methodology, and Centre for Methodology and Informatics. Work In 2007, he proposed a solution to the generalized valued blockmodeling by introducing homogeneity blockmodeling with the basic idea "that the inconsistency of an empirical block with its ideal block can be measured by within block variability of appropriate values". The newly-formed ideal blocks, which are appropriate for blockmodeling of valued networks, are then presented together with the definitions of their block inconsistencies. He also (in 2007/08) developed an implicit blockmodeling approach, based on previous work of Batagelj a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
