5. Running Metrics, Filters, and Timelines | Gephi Cookbook

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Table Of Contents

Gephi Cookbook

5 (1)

Gephi Cookbook

5 (1)

Overview of this book

If you want to learn network analysis and visualization along with graph concepts from scratch, then this book is for you. This is ideal for those of you with little or no understanding of Gephi and this domain, but will also be beneficial for those interested in expanding their knowledge and experience.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Sections

Conventions

Reader feedback

Customer support

Free Chapter

1. Getting Started with Gephi

1. Getting Started with Gephi

Introduction

Installing Gephi

Troubleshooting the Gephi installation

Exploring Gephi's graphical user interface

The basics of working in the Overview mode

The basics of working in the Data Laboratory mode

The basics of working in the Preview mode

2. Basic Graph Manipulations

2. Basic Graph Manipulations

Introduction

Generating a random graph

Selecting and highlighting nodes in the graph

Coloring and sizing nodes in the graph

Adding nodes and edges to the graph

Editing node attributes in the graph

Finding out the shortest path in the graph

Setting the edge and label properties

Setting basic properties for graphs, nodes, edges, and labels

Changing the background color of the graph

Generating a heat map for the graph

Showing convex hulls for a graph where a hierarchy exists

Showing/hiding various parts of the graph

Reverting changes in the graph to the original presets

Creating a PNG file directly from the graph window in user-specified sizes

3. Using Graph Layout Algorithms

3. Using Graph Layout Algorithms

Introduction

Using the Clockwise Rotate layout algorithm

Using the Counter-Clockwise Rotate layout algorithm

Using the Contraction layout algorithm

Using the Expansion layout algorithm

Using the Force Atlas layout algorithm

Using the Force Atlas 2 layout algorithm

Using the Fruchterman Reingold layout algorithm

Using the Label Adjust layout algorithm

Using the Random Layout algorithm

Using the Yifan Hu layout algorithm

Using the Yifan Hu Proportional layout algorithm

Using the Yifan Hu Multilevel layout algorithm

4. Working with Partition and Ranking Algorithms

4. Working with Partition and Ranking Algorithms

Introduction

Partitioning the graph based on node attributes

Partitioning the graph based on edge attributes

Configuring node colors in a graph by ranking nodes

Configuring node sizes in a graph by ranking nodes

Configuring node label colors in a graph by ranking nodes

Configuring node label sizes in a graph by ranking nodes

Configuring edge colors in a graph by ranking edges

Configuring the colors of edge labels in a graph by ranking edges

Configuring the size of edge labels in a graph by ranking edges

5. Running Metrics, Filters, and Timelines

5. Running Metrics, Filters, and Timelines

Introduction

Selecting a list of metrics for a graph

Finding the average degree and average weighted degree of a graph

Finding the network diameter

Finding graph density

Finding the HITS value for a graph

Finding a graph's modularity

Finding a graph's PageRank

Finding connected components in a graph

Getting a node overview of a graph

Getting an edge overview of a graph

Getting dynamic statistics for a graph

Applying individual filters on a graph

Applying a combination of filters on a graph

Filtering dynamic graphs based on time intervals

6. Working in the Data Laboratory Mode

6. Working in the Data Laboratory Mode

Introduction

Importing a spreadsheet

Adding and deleting nodes in a graph

Changing the attributes of an existing node in a graph

Adding and deleting edges in a graph

Changing the attributes of an existing edge in a graph

Adding/deleting columns

Merging columns

Copying data between columns

Filtering, searching, and modifying data based on particular attributes

Creating columns with dynamic regular expression filtering

Exporting a table

7. Getting Graphs and Networks Ready for Preview

7. Getting Graphs and Networks Ready for Preview

Introduction

Previewing and fine-tuning a graph in the Default mode

Previewing and fine-tuning a graph in the Default Curved mode

Previewing and fine-tuning a graph in the Default Straight mode

Previewing and fine-tuning a graph in the Text outline mode

Previewing and fine-tuning a graph in the Black Background mode

Previewing and fine-tuning a graph in the Edges Custom Color mode

Previewing and fine-tuning a graph in the Tag Cloud mode

Exporting a graph in the SVG, PNG, or PDF format

8. Exploring Dynamic and Multilevel Graphs

8. Exploring Dynamic and Multilevel Graphs

Introduction

Building dynamic/temporal graphs in Gephi

Working with dynamic/temporal graphs

Working with multilevel graphs

Expanding and contracting subgraphs in metanodes

Clustering links and attributes

9. Getting Real-world Graph Datasets

9. Getting Real-world Graph Datasets

Introduction

Exploring the Web and Internet domain – EuroSiS Web mapping study

Exploring the Web and Internet domain – the Internet dataset

Exploring social networks – Zachary's karate club dataset

Exploring social networks – Twitter's mentions and retweets dataset

Exploring biological networks – the C. Elegans neural network dataset

Exploring biological networks – the yeast dataset

Exploring the infrastructure domain – the airlines dataset

Importing data from MySQL databases

Importing data from Neo4j databases

Importing data via NodeXL

10. Exploring Some Useful Gephi Plugins

10. Exploring Some Useful Gephi Plugins

Introduction

Exporting networks on the Web using Seadragon

Exporting rich interactive visualizations using Sigma.js

Describing complex network structures using GEXF

Generating world maps

Performing social network analysis

Index

Index

Finding a graph's modularity

The modularity of a graph is a measure of its strength and describes how easily the graph could be disintegrated into communities, modules, or clusters. In this recipe, the concept of modularity, along with its implementation in Gephi, is described.

How to do it…

To obtain the modularity score for a graph, follow these steps:

Load the Les Misérables graph in Gephi.
In the Network Overview tab under the Statistics panel, hit the Run button adjacent to Modularity.
In the Modularity settings window, enter a resolution in the textbox depending on whether you want a small or large number of communities:
You can choose to randomize to get a better decomposition of the graph into communities, but this increases the computation time.
You can also choose to include edge weight in computing modularity.
Hit OK once done.
This opens up the Modularity Report window, which the size distribution of communities into various modularity classes. The report also shows the number of communities...

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