Welcome to the world of Gephi, the open source network graph and analysis tool. If you aren't already familiar with Gephi, this chapter will provide you a brief primer on both Gephi and the many ways in which it can be used to address real-world network analysis. For those who are already familiar with the software, this section will inspire you to take advantage of the many opportunities provided by this powerful tool.
Advances in computing power have helped to revolutionize the science of network graph analysis by putting complex datasets into the hands of thousands of users, and thus leading to the evolution of tools that help practitioners make sense out of previously unmanageably large datasets. Gephi is one of the tools at the forefront of this revolution, with a growing user community that produces some exceptional visualization. Gephi is far more than just a tool for producing attractive graphs; it is also a powerful instrument for exploratory data analysis that enables users to learn more about a given network.
This chapter will cover the following topics:
First, we will examine a range of graph applications that represent some of the many ways we might choose to use Gephi in order to address real-world data
The next section will provide an overview of the network graph vernacular, which will cover the primary topics of connectivity, network structure, and network behaviors
Finally, we will begin to explore how we can use Gephi as the primary toolkit to move from the conceptual realm into a very hands-on, real-world application
Note that this chapter and the remainder of the book are focused solely on the Gephi desktop software, and not the Gephi toolkit. The toolkit provides Java library modules that can be plugged into new Java applications to deliver core Gephi functionality. More information on the toolkit can be found online at http://gephi.github.io/toolkit/.
Let's get started with some potential applications that will begin to illustrate the number of ways in which we can use Gephi to create compelling network analysis and visualization.