Network analysis literature is filled with many examples of how networks grow over time. Multiple models have been developed to explain the growth of networks, as these patterns differ substantially depending on the sort of network we are analyzing. Network growth has been the subject of a great deal of research and analysis and will not be covered to the same degree in this book. In its place, I will provide an overview of some of the primary growth theories, and set the table for further exploration using Gephi later in this chapter.

What we attempt to understand through observing and predicting network growth is how networks form, how they are likely to grow, and what sort of patterns they exhibit as they are growing. Multiple models exist that attempt to predict network growth using different algorithms, ranging from extremely simple (random graph models) through much more sophisticated approaches that use concepts such as preferential attachment and popularity...