In this chapter, you have seen numerous examples of some of the primary patterns that are fundamental to the study of network graph analysis.

We began the chapter with theoretical discussions on the critical processes of contagion, diffusion, clustering, homophily, and network growth. A number of network growth examples were created using the Complex Generators plugin, providing a fundamental understanding of how to use this tool to construct and analyze multiple network models.

In the last few sections of this chapter, our focus was on implementation of some of these concepts using the Gephi workspace. We first created a contagion network that viewed the progression of an infection over a three-day time period, followed by a simple diffusion process that tracked product adoption within a small network. Finally, we addressed network clustering and homophily, showing some examples that illustrated relative levels of each of these within a network.

Our next chapter will be devoted to mastering Gephi filters, a powerful set of tools that can be used to provide focus and develop insights when working with large datasets.