Andrej Mrvar

Last updated
Andrej Mrvar
Nationality Slovenian
Alma mater
Scientific career
Fields Computer Science
Institutions University of Ljubljana
Thesis Analiza in prikaz velikih omrežij  (1999)
Doctoral advisor Vladimir Batagelj
Saša Divjak
Website http://mrvar.fdv.uni-lj.si/

Andrej Mrvar is a Slovenian computer scientist and a professor at the University of Ljubljana. [1] He is known for his work in network analysis, graph drawing, decision making, virtual reality, electronic timing and data processing of sports competitions. [2]

Contents

Education and career

He is well known for his work on Pajek, [3] a free software for analysis and visualization of large networks. [4] Mrvar began work on Pajek in 1996 with Vladimir Batagelj.

His book Exploratory Social Network Analysis with Pajek, coauthored with Wouter de Nooy and Vladimir Batagelj, is his most cited work. It was published by Cambridge University Press in three editions (first 2005, second 2011, and third 2018). [4] The book was translated into Japanese (2009) and Chinese (first edition 2012, second 2014).

With Anuška Ferligoj, he was a founding co-editor-in-chief of the Metodološki zvezki journal. [5]

Awards and honors

Selected publications

Related Research Articles

<span class="mw-page-title-main">Vladimir Batagelj</span> Slovenian mathematician

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).

<span class="mw-page-title-main">Social network analysis</span> Analysis of social structures using network and graph theory

Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes and the ties, edges, or links that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, meme spread, information circulation, friendship and acquaintance networks, peer learner networks, business networks, knowledge networks, difficult working relationships, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through sociograms in which nodes are represented as points and ties are represented as lines. These visualizations provide a means of qualitatively assessing networks by varying the visual representation of their nodes and edges to reflect attributes of interest.

<span class="mw-page-title-main">Graph drawing</span> Visualization of node-link graphs

Graph drawing is an area of mathematics and computer science combining methods from geometric graph theory and information visualization to derive two-dimensional depictions of graphs arising from applications such as social network analysis, cartography, linguistics, and bioinformatics.

<span class="mw-page-title-main">Mathematical sociology</span> Interdisciplinary field of research

Mathematical sociology is an interdisciplinary field of research concerned with the use of mathematics within sociological research.

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.

Cultural analytics refers to the use of computational, visualization, and big data methods for the exploration of contemporary and historical cultures. While digital humanities research has focused on text data, cultural analytics has a particular focus on massive cultural data sets of visual material – both digitized visual artifacts and contemporary visual and interactive media. Taking on the challenge of how to best explore large collections of rich cultural content, cultural analytics researchers developed new methods and intuitive visual techniques that rely on high-resolution visualization and digital image processing. These methods are used to address both the existing research questions in humanities, to explore new questions, and to develop new theoretical concepts that fit the mega-scale of digital culture in the early 21st century.

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.

<span class="mw-page-title-main">Gephi</span> Network analysis and visualization software package

Gephi is an open-source network analysis and visualization software package written in Java on the NetBeans platform.

<span class="mw-page-title-main">NodeXL</span> Network analysis and visualization package for Microsoft Excel

NodeXL is a network analysis and visualization software package for Microsoft Excel 2007/2010/2013/2016. The package is similar to other network visualization tools such as Pajek, UCINet, and Gephi. It is widely applied in ring, mapping of vertex and edge, and customizable visual attributes and tags. NodeXL enables researchers to undertake social network analysis work metrics such as centrality, degree, and clustering, as well as monitor relational data and describe the overall relational network structure. When applied to Twitter data analysis, it showed the total network of all users participating in public discussion and its internal structure through data mining. It allows social Network analysis (SNA) to emphasize the relationships rather than the isolated individuals or organizations, allowing interested parties to investigate the two-way dialogue between organizations and the public. SNA also provides a flexible measurement system and parameter selection to confirm the influential nodes in the network, such as in-degree and out-degree centrality. The software contains network visualization, social network analysis features, access to social media network data importers, advanced network metrics, and automation.

<span class="mw-page-title-main">Main path analysis</span> Mathematical tool

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.

<span class="mw-page-title-main">Faculty of Social Sciences, Ljubljana</span>

Faculty of Social Sciences is one of the faculties, comprising the University of Ljubljana. It is located at Kardeljeva ploščad.

<span class="mw-page-title-main">Blockmodeling</span> Analytical method for social structure

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.

Patrick Doreian is an American mathematician and social scientist, whose specialty is network analysis. His specific research interests include blockmodeling, social structure and network processes.

<span class="mw-page-title-main">Signed network</span>

In a social network analysis, a positive or a negative 'friendship' can be established between two nodes in a network; this results in a signed network. As social interaction between people can be positive or negative, so can be links between the nodes.

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.

References

  1. FDV.uni–lj.si – Andrej Mrvar
  2. 1 2 3 4 Mrvar.FDV–uni.lj.si – Curicculum Vitae
  3. "Pajek" . Retrieved September 26, 2019.
  4. 1 2 "Vladimir Batagelj is 70". Ars Mathematica Contemporanea. Retrieved September 27, 2019.
  5. "Metodološki zvezki – Advances in Methodology and Statistics" . Retrieved 24 August 2021.
  6. "Hall of Fame". Graph Drawing Contests. Retrieved September 26, 2019.
  7. "William D. Richards Jr., Software Award (Biennial)". International Network for Social Network Analysis. Archived from the original on 2019-09-27. Retrieved September 26, 2019.