Multivariate Network Visualization

Multivariate Network Visualization PDF

Author: Andreas Kerren

Publisher: Springer

Published: 2014-04-15

Total Pages: 244

ISBN-13: 3319067931

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This book is the outcome of the Dagstuhl Seminar 13201 on Information Visualization - Towards Multivariate Network Visualization, held in Dagstuhl Castle, Germany in May 2013. The goal of this Dagstuhl Seminar was to bring together theoreticians and practitioners from Information Visualization, HCI and Graph Drawing with a special focus on multivariate network visualization, i.e., on graphs where the nodes and/or edges have additional (multidimensional) attributes. The integration of multivariate data into complex networks and their visual analysis is one of the big challenges not only in visualization, but also in many application areas. Thus, in order to support discussions related to the visualization of real world data, also invited researchers from selected application areas, especially bioinformatics, social sciences and software engineering. The unique "Dagstuhl climate" ensured an open and undisturbed atmosphere to discuss the state-of-the-art, new directions and open challenges of multivariate network visualization.

Egocentric Network Analysis

Egocentric Network Analysis PDF

Author: Brea L. Perry

Publisher: Structural Analysis in the Soc

Published: 2018-03-22

Total Pages: 371

ISBN-13: 110713143X

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An in-depth, comprehensive and practical guide to egocentric network analysis, focusing on fundamental theoretical, research design, and analytic issues.

Visual Analysis of Multilayer Networks

Visual Analysis of Multilayer Networks PDF

Author: Fintan McGee

Publisher: Morgan & Claypool Publishers

Published: 2021-06-10

Total Pages: 152

ISBN-13: 1636391443

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This is an overview and structured analysis of contemporary multilayer network visualization. It surveys techniques as well as tools, tasks, and analytics from within application domains. It also identifies research opportunities and examines outstanding challenges along with potential solutions and future research directions for addressing them. Visual Analysis of Multilayer Networks is not only for visualization researchers, but for those who need to visualize multilayer networks in the domain of complex systems, as well as anyone solving problems within application domains. The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization.

Fundamentals of Brain Network Analysis

Fundamentals of Brain Network Analysis PDF

Author: Alex Fornito

Publisher: Academic Press

Published: 2016-03-04

Total Pages: 496

ISBN-13: 0124081185

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Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain

Network Analysis and Visualization in R

Network Analysis and Visualization in R PDF

Author: Alboukadel Kassambara

Publisher: STHDA

Published: 2017-11-26

Total Pages: 39

ISBN-13: 1981179674

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Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks. This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs. - Detect important or central entities in a network graph. - Detect community (or cluster) in a network.

Lattice

Lattice PDF

Author: Deepayan Sarkar

Publisher: Springer Science & Business Media

Published: 2008-02-15

Total Pages: 283

ISBN-13: 0387759697

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Written by the author of the lattice system, this book describes lattice in considerable depth, beginning with the essentials and systematically delving into specific low levels details as necessary. No prior experience with lattice is required to read the book, although basic familiarity with R is assumed. The book contains close to 150 figures produced with lattice. Many of the examples emphasize principles of good graphical design; almost all use real data sets that are publicly available in various R packages. All code and figures in the book are also available online, along with supplementary material covering more advanced topics.

Statistical Analysis of Network Data with R

Statistical Analysis of Network Data with R PDF

Author: Eric D. Kolaczyk

Publisher: Springer

Published: 2014-05-22

Total Pages: 214

ISBN-13: 1493909835

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Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

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