Earlier in this chapter, we discussed the concept of clustering in a network, and some of the ramifications for network structure and information flow. In this section, we'll use Gephi to provide you with some illustrations of networks with varying degrees of clustering, and add some further discussion on how Gephi can be leveraged to identify and measure clustering.

In the interest of clarity, I would like to take a moment to define clustering. When I refer to clustering in this section, it indicates the patterns that exist within a network, not the practice of creating clusters from the data. While the two instances are frequently related, this section is devoted to understanding why these patterns exist, and how they might affect the flow of information within a network. Later in this book we'll examine how to create clusters or partitions within the network through the use of defining characteristics in the data. These topics will be addressed in Chapter 7, Segmenting...