While I have used networks in the past to better illustrate potential connections between sites (and populations) based largely upon similarity indices, I am also using networks to explore epistemological issues that articulate with a number of our projects. These models continue to be used in exploratory analyses as a method of generating hypotheses that we can use in our confirmatory analyses.
Adopting methods from scientometrics, bibliometrics and machine learning has helped to mine the literature associated with geometric morphometrics as well as predictive modeling in archaeology. These methods aid in crafting a deeper understanding of how the various arguments in each research domain are structured, helping to identify resources that may be useful in this research program. The bipartite citation networks are filtered by a degree of two, and use a modularity algorithm to identify communities of practice within the network.
Further still, network analysis is being used to take a closer look at the variable legal challenges that employ laws associated with cultural resources and heritage management. This has proven to be a useful tool in identifying those trends associated with the legal responses through time.
The contribution of network analysis to the study of archaeology is substantial, although the full scope of applications remains unclear. Within the context of those research domains mentioned above, it offers a substantive contribution that challenges a number of our ideas, while reinforcing others.
“That is what learning is. You suddenly understand something you’ve understood all your life, but in a new way.” –Doris Lessing (Nobel Laureate)