Mastering Gephi Network Visualization电子书

Mastering Gephi Network Visualization

Table of Contents

Mastering Gephi Network Visualization

Credits

About the Author

Acknowledgments

About the Reviewers

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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 school network with dynamic edges

Using Gephi to explore the network

Creating the project as a PDF

Anticipating the future of network analysis

Summary

A. Data Sources and Other Web Resources

Data sources

Web resources

Import processes

Bibliography

Index