Mastering Gephi Network Visualization
Gephi has rapidly become one of the most utilized tools for the exploration and
analysis of network data, as users seek to understand the relationships between
groups of people, institutions, events, and other connected phenomena. At the same
time, Gephi can help us understand serious topics such as disease transmission, the
diffusion of ideas and innovation, and changes over time to community structures.
With the ability to import a wide variety of data formats both open and proprietary,
Gephi is truly moving toward democratizing network information.
This book aims to assist both new and experienced users in fully leveraging the
immense potential of Gephi, regardless of whether the end goal is exploration,
analysis, visualization, or some combination of each. While not every nuance of
Gephi is covered in this volume, the topics in the book should go a long way toward
improving your capabilities for effectively using Gephi.
What this book covers
Chapter 1, Fundamentals of Complex Networks and Gephi, provides background into
the world of complex networks and how we can use Gephi to explore and analyze
Chapter 2, A Network Graph Framework, provides a process for creating and
developing network visualizations using Gephi.
Chapter 3, Selecting the Layout, will introduce many available layout algorithms in
Gephi, and help you to select the most appropriate types based on the characteristics
of your network data.
Chapter 4, Network Patterns, examines several critical network patterns, including
contagion, diffusion, and homophily. We then use Gephi to explore and understand
Chapter 5, Working with Filters, provides multiple examples for how and when to use
the powerful filtering capabilities provided within Gephi.
Chapter 6, Graph Statistics, provides readers with background on some key statistical
network measures, followed by examples for how to effectively apply these methods
Chapter 7, Segmenting and Partitioning a Graph, provides insight into the multiple
approaches that can be used to effectively segment a network, based on categorical
or behavioral attributes. The use of size and color to partition a graph will be
Chapter 8, Dynamic Networks, will introduce the concept of Dynamic Network Analysis
(DNA) and how time-based networks can be explored and understood in Gephi.
Chapter 9, Taking Your Graph Beyond Gephi, gives an overview of available export
options, followed by several examples for creating visualizations by combining
Gephi with external tools.
Chapter 10, Putting It All Together, incorporates many of the methods covered earlier
in the book to create both revised and brand new visualizations. We’ll also introduce
some new methods that will allow for further network customization.
Who this book is for
This book is designed for those who would like to use Gephi to view, explore, and
analyze network data. It will also be valuable for those who wish to create network
visualizations that can be deployed beyond Gephi, as static or web-based interactive
versions. Both relatively inexperienced users as well as Gephi power users
should find material that will make Gephi a more powerful tool for working
with network data.