<span>The adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering. However, until now, no book has dealt exclusively with the
Multilayer Networks: Analysis and Visualization: Introduction to muxViz with R
β Scribed by Manlio De Domenico
- Publisher
- Springer
- Year
- 2022
- Tongue
- English
- Leaves
- 124
- Edition
- 1st ed. 2022
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering. However, until now, no book has dealt exclusively with the analysis and visualization of multilayer networks.Β Multilayer Networks: Analysis and VisualizationΒ provides a guided introduction to one of the most complete computational frameworks, named muxViz, with introductory information about the underlying theoretical aspects and a focus on the analytical side. Dozens of analytical scripts and examples to use the muxViz library in practice, by means of the Graphical User Interface or by means of the R scripting language, are provided.Β
β¦ Table of Contents
Foreword
Preface
Acknowledgements
Contents
Figures and plots
Boxes
Code Snippets
Acronyms
Part I Multilayer Network Science: Analysis and Visualization
Chapter 1 Introduction
1.1 Mathematical representation of a complex network
1.2 Multilayer networks: towards a more realistic model of complex systems
1.3 Structure of multilayer networks
1.4 Dynamics on and of multilayer networks
1.5 muxViz: A tool for data science of multilayer networks
Chapter 2 Multilayer Networks: Overview
2.1 Multilayer network models
2.2 Representing multilayer networks
2.3 Fundamental tensors
2.4 Dynamical processes
Chapter 3 Multilayer Analysis: Fundamentals and Micro-scale
3.1 Descriptive statistics per layer
3.2 Aggregate network
3.3 Layer-layer correlations
3.4 Network of layers
3.5 Multilayer walks, trails, paths, cycles and circuits
Chapter 4 Multilayer Versatility and Triads
4.1 Node centrality in multilayer networks
4.1.1 Multilayer degree and strength centralities
4.1.2 Multilayer Katz centrality
4.1.3 Multilayer HITS centrality
4.1.4 Multilayer PageRank centrality
4.1.5 Multilayer kβcoreness centrality
4.1.6 Multilayer Closeness centrality
4.1.7 Application to fictional social networks
4.2 Multilayer motifs
4.3 Multilayer triadic closure
Chapter 5 Multilayer Organization: Meso-scale
5.1 Multilayer connected components
5.2 Multilayer communities and modules
5.3 Clustering and reducing multilayer structures
Chapter 6 Other Multilayer Analyses Based on Dynamical Processes
6.1 Navigability of multilayer systems
6.2 Functional reducibility of multilayer systems
Chapter 7 Visualizing Multilayer Networks and Data
7.1 Embedding nodes and layers in a 3D space
7.2 Annular visualization of multivariate data
Part II Appendices
Chapter A Installing and Using muxViz
A.1 The "Universe" of muxViz
A.2 Requirements and Installation for v3.1 (LIB)
A.3 Requirements and Installation for v2.0 (GUI)
A.4 oubleshooting
A.4.1 Very quick installation on GNU/Linux
A.4.2 Ubuntu 14.04
A.4.3 Multimap or FANMOD not found
A.4.4 Possible errors when using Motifs
A.4.5 Possible errors with rgdal
A.4.6 Possible errors with rjava (any OS)
A.4.7 Possible errors with rjava (latest MacOSs)
A.4.8 Install muxVizwith R 3.3 or higher
A.4.9 Use existing Linear Algebra Library
A.5 Preparing the data: allowed formats
A.5.1 Edge-colored networks
A.5.2 Non-edge-colored networks
A.5.3 Standard edges list
A.5.4 Extended edges list
A.5.5 Format of a layout file
A.5.6 Format of a layer-info file
A.7 Format of a timeline file
References
Glossary
π SIMILAR VOLUMES
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<p></p><p><span>The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. A huge open-source project, R has become enormously popular because of its power and flexibility. With R you can organise, analyse and visua
<p><span><p>The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. A huge open-source project, R has become enormously popular because of its power and flexibility. With R you can organise, analyse and vis
<p>Gephi is a great platform for analyzing and turning your data into highly communicative visualizations, and this book will teach you to create your own network graphs, and then customize and publish them to the web. </p> <p><b>Overview</b></p> <ul> <li>Use your own data to create network graphs d