Last week, because of a tweet by Alan Liu, I found Scott Weingart’s wonderful digital humanities blog. As it turns out, it looks like he had already gone through some of the same work processes last year, that I codified last month by adding a .gexf export function to Neal Caren’s refcliq.
One of the things I learned from scott’s post was that I had been drawing co-citational, rather than citational, graphs. Which made a lot of sense of the structures I’d been seeing. Basically, a line on the graph btw A and B doesn’t represent work A citing work B, but instead that A and B are both cited by some third work, not necessarily represented on the graph. All the nodes you have seen in the graphs I have posted are works that have been cited two or more times, and the edges are all representations that those two works have been cited together by two or more separate articles.
What was missing from these exports was the temporal dimension: co-citational network graphs allows us to think visually about how fields organize knowledge, and their own production of it. However, the interactive graphs I published before were static, and so did not allow us to think about how these internal structures developed over time.
I therefore reworked the code to export dynamic graphs (.gexf format only). These graphs register changes in influence and connectedness, over time, of the works cited by a journal.
I believe I wrote this code properly, but it is producing small variances in graph sizes compared to Caren’s original, so if anyone is interested in helping to unpack that, definitely email me. I also considered the usefulness of making modularity classes dynamic,
Back to the graph. My test case is again Studies in Romanticism. Over time, you will see individual nodes and edges changing size based on (respectively) the number of times a given work has been cited, and the number of times two works have been cited together. You will also see clusters develop, and separate from one another. I have not added any decay function, so once works are linked, or once a work has a specific node size, it either keeps that size or grows; no works or links diminish in absolute terms simply because they haven’t been cited in a while.
In relative terms, however, they may fail to keep up with the growing influence of Wordsworth’s Prelude, Coleridge’s Biographia Literaria, or even Milton’s Paradise Lost. I have identified clusters around the big six poets, plus three around Mary Shelley, William Godwin, and Walter Scott. I have also identified the developments of two of these sub-areas of Romantic interest with the publications of major critical works (all shown on graph).
Here is my annotated video screen capture of the dynamic graph’s development over time.
I really think this kind of visualization could be an incredible research aid, if the raw data were cleaned up. But other commitments are likely going to keep me from working on this project for a while. In the meantime, please consider developing the code on GitHub and/or use the tool to create a map of your own field’s evolution. If you do, please email me a link to give me a few minutes’ break 🙂