I explored the social network DH project called the Six degrees of Francis Bacon. In the network, the edges are personal relationships, and the nodes are people Francis Bacon had a connection with. The value of the node color and node size indicates the degree of separation between the person and Francis Bacon. A grey edge indicates that the relationship is statistically inferred while a black edge indicates a user-contributed relationship.
Overall, the project is very interactive. I can drag nodes around and click an edge or a node to change the information pop up. There is also a way to isolate nodes such that only their relationships are visible on the web page. I can zoom in and out which allows me to explore even the smallest nodes or view the overwhelming network. There are also different features and filters I can use. For example, exporting the data into a table or filtering the data by visual density. This level of interactivity is helpful because it allows me to separate bigger figures from minor ones and adjust the clarity of the network. With all nodes and edges visible, the web application can be a little bit laggy. Thus, being able to adjust the relationship confidence level, date range, or visual density can help with navigation for people with slower systems. On the other hand, being able to adjust so many settings can be a little intimidating at first. Especially when using the concentric visualization layout, navigating via edges for degrees greater than 1 is very difficult as there is too much overlap.
The DH project is an open collaboration where scholars and students from all over the world can contribute to and expand. The project started between Carnegie Mellon University and Georgetown University. The web application is made up of a Ruby on Rails backend and an AngularJS frontend. It incorporates text mining techniques along with network analysis to extract and infer connections based on historical texts.
