The initial report from the project can be found here. The network approach allows us to focus our attention primarily on the interactions within any given system, whether that be a world of letters, journeys etc. The bigger the data however, the harder it is to deal with. This database is currently one corpus of letters–-there are 600 letters-–centered around one particularly important figure at the time, George Melville, Lord Melville, the Secretary of State for Scotland. The letters exchanged in this period are more than just networks of correspondence; people were bound together through community, print, and dialogue. Exchanging letters in a period of chaotic and often violent warfare was even more complex. Context is everything in understanding people, groups, identity, and behavior in the early modern world. Given this, understanding the relationships is paramount to visualizing the data. Behavior, relationships, and identity changed over the course of the Revolution and Networking Letters of the Revolution sought to trace those changes and connect historical networks with visual interpretation by building a new database and visual representation of the interconnected nature of communication. In the last 25 years, there has been a noticeable shift from historical records remaining piecemeal or fragmented in boxes in archives to a sea of digitized images and texts in the form of PDFs or PNGs. A number of manuscripts are now available online, including the Leven and Melville Papers. Our goals in this project were to:
This project is a marriage of early modern Scottish history and computational data science. It brings together methods of network science, prosopography, and traditional early modern political history surrounding communication. The visualizations show a story of connectivity over time. We chose this particular corpus of letters because Leven and Melville Papers do a very good job at capturing the difficulties in the reconstruction and administration of Scottish governance during such a chaotic period.
Phase one required turning qualitative data into quantitative data. We started by recording all of the pertinent data from the PDF version of the Leven and Melville Papers. We then turned this data into spreadsheet data, here we used categories: Id, Sender, Receiver, Location from, Location to, Latitude and Longitude, Type and Date. This allowed us to parse the networking data in the form of nodes and edges. The data was then cleaned using OpenRefine to split up latitude and longitude and keywords into different columns; we also made sure there were no blank tiles and duplicates. After creating a master spreadsheet information file, we then set about creating different sheets for different visualizations including people, places, keywords, nodes, and then edges (relationships). We were able to get all the data from the 599 letters contained in the digitized copy of the Leven and Melville papers into a csv file. Given the large dataset of Network Letters, it allowed for exploratory data analysis and investigation on different digital tools to identify the best representation of the relationships presented in the papers. One of the main tools we ended up using was the programming language Python; which contains a large number of libraries that extend the capabilities of the language, allowing for complex visualizations of the Network Data. One of the most prominent libraries used was networkx, which allowed the creation of network graphs along with the application of the Girvan-Newman algorithm to detect communities within the network. This algorithm works by repeatedly removing edges on the shortest path within the network. Additionally, the nodes are given corresponding colors to highlight their community, enabling an easier identification of groups in the network. The algorithm is important for understanding the network graph because a node with higher betweenness centrality would have more control over the network, due to the fact that more information will pass through that node. The implementation of these libraries and creation of visuals were carried out on Jupyter notebook, which is an open-source software for interactive computing. In addition, we experimented with tools such as Leaflet, Flourish, and Gephi for further analysis of the letters.
What we have found within this corpus is 123 unique senders and receivers; each was assigned metadata in the form of their allegiance, cabinet position, and weight. We found 554 individual letters, packets, orders, sets of instructions, declarations, commissions, attestations, memorials, intercepted letters, and more. The corpus also contained 72 places of origin and target which were then geocoded. We aregues similarly to Ruth and Sebastian Ahnert's suggestions that network hubs correspond broadly with the centers of government.2 This also includes somewhat symbolic hubs of the monarch and the principal secretaries. There are imbalances present throughout the corpus especially since more letters received survive than letters sent. If there was a complete record of the correspondence there would be less imbalance. There are also intercepted letters present in the collection which might account for some of the anomalies in the network.
After some initial calculations and experimentations, we argue that based on the letters contained in the corpus the most connected nodes are Melville, King William, Queen Mary, William Lockhart, the Earl of Crawford, the Earl of Leven, Colonel Hill, and the Privy Council. This is unsurprising since the monarch and their principal secretaries tend to be the same epistolary hub. The Earl of Crawford and the Privy Council served as the primary contacts for the Scottish administration for much of the time period. William Lockhart served as Solicitor General for Scotland from 1689 to 1693 and was the King's principal legal advisor for Scottish affairs. Leven and Hill served as the governors of Edinburgh Castle and Fort William (Inverlochy) and had many military connections and networks. That these are the most connected nodes speaks to the amount of letters that were exchanged about the evolving situation in Scotland. Despite instructions contained within many of the letters, which told the receiver to burn the letter received, correspondence from the period has survived. In aggregate it shows that despite previous assertions that William was not interested what was going on in his northern kingdom we can argue that this seems not to be the case.