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Mastering Gephi Network Visualization
Ken Cherven
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eBook - ePub
Mastering Gephi Network Visualization
Ken Cherven
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Information
Mastering Gephi Network Visualization
Table of Contents
Mastering Gephi Network Visualization
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why subscribe?
Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the color images of this book
Errata
Piracy
Questions
1. Fundamentals of Complex Networks and Gephi
Graph applications
Collaboration graphs
Who-talks-to-whom graphs
Information linkages
Technological networks
Natural-world networks
A network graph analysis primer
Paths and connectivity
Paths
Cycles
Connectivity
Network structure
Centrality
Components
Giant components and clustering
Homophily
Density
Network behaviors
Contagion and diffusion
Network growth
Overviewing Gephi
Primary windows
Data laboratory
Manual entry
CSV import
Excel import
MySQL import
Graph file import
Graph window
Preview window
Secondary windows – tabs
The filtering tab
The statistics tab
The layouts tab
Essential plugins
Clustering – Chinese Whispers
Data laboratory
Data laboratory helper
Exports
Sigma.js Exporter
Seadragon Web Export
Graph Streaming
ExportToEarth
Generator – the Complex Generators plugin
Layout
The Multipartite layout
The Hiveplot layout
The Concentric layout
The OpenOrd layout
The Circular layout
The Layered layout
The ARF layout
Additional plugins
Link Communities – metrics
Give color to nodes – tools
Summary
2. A Network Graph Framework
A proposed process flow
Identifying an idea or topic
Determining the final output
Identifying the data sources
Formatting the data for Gephi
Importing data into Gephi
Viewing the initial graph layout
Selecting a layout
Analyzing the graph
Modifying the graph
Exporting the graph
Creating an example graph
Identifying the topic
Finding the data source
Formatting the data for Gephi
Importing the data
Viewing the initial network
Selecting an appropriate layout
The Force Atlas layout
The Fruchterman-Reingold layout
The Radial Axis layout
The Yifan Hu layout
ARF
Analyzing the graph
Modifying the graph
Exporting the graph
Summary
3. Selecting the Layout
Overviewing the layout types
Force-based layouts
The ARF layout
Force Atlas
Force Atlas 2
Force Atlas 3D
The Fruchterman-Reingold algorithm
The OpenOrd algorithm
The Yifan Hu algorithm
The Yifan Hu Proportional layout
The Yifan Hu multilevel approach
Tree layouts
DAG layout
Circular layouts
The Circular layout
The Concentric layout
The Dual Circle layout
Radial layouts
The Hiveplot layout
The Radial Axis layout
Geographic layouts
The Geo layout
The Maps of Countries layout
Additional layouts
The Isometric layout
The Multipartite layout
The Layered layout
Network Splitter 3D
Additional layout tools
Assessing your graphing needs
Actual example – the Miles Davis network
Analysis goal
Dataset parameters
Network density
Network behaviors
Network display
Temporal elements
Interactivity
Layout strengths and weaknesses
Testing layouts
Testing the ARF layout
The Concentric layout
Testing the Radial Axis layout
Layout selection criteria
Graph aesthetics
Working example of graph aesthetics
Summary
4. Network Patterns
Contagion and diffusion
Contagion
The SIR model
The SIS model
The SIRS model
Diffusion
Clustering and homophily
Clustering
Homophily
Network growth patterns
Using Gephi generators
Viewing a contagion network
Viewing network diffusion
Network clustering
Identifying homophily
Summary
5. Working with Filters
The filtering theory
Primary filtering functions in Gephi
Attributes
Edges
Operator
Topology
Using simple filters
Using the Equal filter
Applying the regex function
Filtering edges
Using the Partition filter
Working with the Topology filters
Working with complex filters
Applying multiple filter conditions
Using subfilters
Working with Mask and Intersection conditions
Working with the UNION operator
Summary
6. Graph Statistics
Overview of graph statistics
Network measures
Diameter
Eccentricity
Graph density
Average path length
Connected components
Erdos number
HITS
Edge betweenness
Centrality measures
Degree centrality (undirected graphs)
In-degree centrality (directed graphs)
Out-degree centrality (directed graphs)
Closeness centrality
Eigenvector centrality
Betweenness centrality
Clustering and neighborhood measures
Clustering coefficient
Number of triangles
Modularity
Link Communities
Neighborhood overlap and embeddedness
Interpreting graph statistics
Interpreting network measures
Interpreting centrality statistics
Degree centrality
In-degree centrality
Out-degree centrality
Closeness centrality
Eigenvector centrality
Betweenness centrality
Interpreting clustering statistics
Interpreting clustering coefficients
Number of triangles
Modularity
Link Communities
Embeddedness
Application of statistical measures
Basic statistical applications
Network statistics
Network diameter
Eccentricity
Graph density
Average path length
Edge betweenness
Centrality statistics
Degree centrality
Closeness centrality
Eigenvector centrality
Betweenness centrality
Clustering statistics
Clustering coefficient
Number of triangles
Modularity
Link Communities
Embeddedness
Filtering using graph statistics
Summary
7. Segmenting and Partitioning a Graph
Partitioning and clustering options
The Partition tab
The Ranking tab
Manual settings
Chinese Whispers
Markov clustering
Partitioning and clustering examples
Partitioning
Working with the Ranking tab
Using color and size options
Manual graph segmentation
Using the Chinese Whispers plugin
Using the Markov Clustering plugin
Summary
8. Dynamic Networks
When to use DNA
Topology-based DNA
Generating a dynamic network
Understanding time intervals
Working with timelines
Preparing and importing data for DNA
Implementing and viewing a dynamic network
Creating time intervals in an existing project
Adding time intervals to a new project
Using an existing GEXF file
Adding multiple timeframes
Working with timelines
Applying the timeline
Timelines as filters
Attribute-based DNA
Preparing the data
Implementing and viewing dynamic attribute networks
Creating dynamic GEXF files
Summary
9. Taking Your Graph Beyond Gephi
Overview of the available tools
Graph file exporters
CSV files
DL files
GDF files
GEXF files
GML files
GraphML files
NET files
VNA files
Image exporters
PNG export
SVG export
Editing an SVG file with Inkscape
PDF export
Editing a PDF file in Inkscape
Web exporters
Seadragon Web Export
Sigma.js Exporter
Loxa Web Site Export
Exporting a web graph
Seadragon
SigmaExporter
Loxa Web Site Export
Summary
10. Putting It All Together
Using Gephi to understand existing networks
Creating new Gephi projects
Project 1 – Newman NetScience dataset
Exploring the network in Gephi
Deploying the project to the Web
Project 2 – high...