One of the projects I’ve been working on this year has been a textual analysis of the fifteenth-century London Chronicles for an English professor’s research. The professor hoped to identify and isolate place names in the text (such as London Bridge, Sussex, etc.) and make a map of all the data. This is where the Digital Humanities team came in: what software and digital tools could we use to extract this data and display it in an insight way?
The first tool we examined was Voyant, an online textual analysis tool that creates data visualizations. We uploaded a PDF of the London Chronicles to Voyant and played around with the website to see how it worked and determine whether it was effective.
While Voyant was great for analyzing macro data sets and getting a holistic view of the text, it was rather ineffective for gathering specific iterations of place names and appeared no better than manual close reading for this purpose. One of the other problems we encountered were the variations in medieval spelling; for example, Voyant created a separate category for “London” and “Londan” even if they referred to the same place.
We then turned to a different tool to help map our place names: Edinburgh Geoparser. Geoparser created a wonderful map of the place names. However, it was unable to quantify the number of times a place name appears or arrange the place names in order of frequency. Thus, it was great for visualizing the places but not ideal for textual analysis.
Finally, after testing these different softwares, we stumbled upon a Gazetteer of Early Modern Europe which contained a list of place names, their spelling variants, and their location. We collaborated with a member of the Data Squad, a local Carleton organization dedicated to organizing data, to produce a program that would cross-reference The London Chronicles PDF with an XML of this data. In this manner, we would be able to get a reliable count of place names in the text that included their spelling variants.
This process has taught me that Digital Humanities is a lot of trial and error. In doing this research, I’ve learned there might not be one perfect tool for a project, but combining different resources and collaborating with others allowed me to find an innovative solution. This experimentation and sharing of ideas and research is vital to the work we do as Digital Humanities Associates.
