Ruth Ahnert and Sebastian E. Ahnert, Tudor Networks of Power. Oxford University Press. 2023. ISBN: 978-0-1988-5897-3. $45.99.
Information about individuals is often interesting and useful, but you gain important insights when you build a network describing the connections between those individuals. When those networks include the truly powerful, such as heads of state, the results can be quite interesting and informative.
In Tudor Networks of Power, published by Oxford University Press, academics Ruth Ahnert and Sebastian E. Ahnert perform advanced network analysis based on letters exchanged among power players from England’s Tudor period. King Henry VIII is probably the most prominent person in the data set, but there are many powerful individuals, influencers, and other players to be accounted for.
The Ahnerts are well-positioned to take on this sort of project in the digital humanities. Ruth Ahnert is a professor of literary history and digital humanities at Queen Mary University, London, while Sebastian E. Ahnert is a university lecturer in chemical engineering at Cambridge. Sebastian has also developed expertise in network analysis, which complements Ruth’s skills well in this project.
I believe Tudor Networks of Power is best thought of as documenting a professional research project in the digital humanities. Working off an analog data source from an era before standardized spelling is a daunting prospect, even before one considers optical character recognition errors. Are Cecyll and Cesill the same person? Which James, Earl of Desmond is mentioned in this letter? There were four, after all. Name disambiguation alone took Ruth Ahnert and her assistants nine months of full-time work and a few more months part-time to complete.
Once the names were rounded into shape the Ahnerts could turn to their network analysis. Individual measures such as degree centrality (the number of incoming and outgoing connections from a network node), betweenness (the number of shortest paths between two network nodes that an individual appears on), and eigenvector centrality (proximity to a powerful node) provide useful data, but these measures provide more insight when combined into a network profile.
A network profile is the set of measures calculated for a specific node on the network. Each node represents a person, so you can identify people who make many connections, those who have a few connections but they are to high-level individuals, and ambassadors or merchants that create bridges between otherwise separated groups. I think of network profiling as a form of cluster analysis, where you identify network nodes that have many traits in common.
I enthusiastically recommend Tudor Networks of Power, especially for grad students and younger researchers in the digital humanities. The authors’ description of this project provides useful information for academics and other analysts who wish to perform network and link analysis, especially on data sets that require significant processing.