John R. Ladd

I’m an Assistant Professor in Computing and Information Studies at Washington & Jefferson College, where I teach and research on the use of data across a wide variety of domains, especially in cultural and humanities contexts. I also build research tools, write data science tutorials, and make small, weird web projects.

In my research I think about the long, interwoven histories of media and technology from the early modern period to today. I’m currently working on a book about social networks and literary collaboration, called Network Poetics, which argues that shifts in the networks of 17th century print production allowed for the emergence of new literary forms.

Some Recent Work

Imaginative Networks: Tracing Connections Among Early Modern Book Dedications. An article for the Journal of Cultural Analytics that uses bibliographic network analysis to help understand the history of early modern print culture.

A visualization from the Imaginative Networks article showing two bipartite networks.

EarlyPrint + Python. A textbook for early modern text analysis in the programming language Python, built as an interactive Jupyter Book. Topics covered include TF-IDF, word vectors, and supervised text classification.

A screenshot from a page of the Jupyter Book, showing a heatmap of word vectors.

Network Navigator. A browser tool for network analysis, with special emphasis on quantitative metrics and less common visualization types. Redesigned in 2021 with Zoe LeBlanc.

A screenshot of Network Navigator, showing metrics and visualizations for a Game of Thrones network dataset.

Exploring Linked Art. A series of tutorials, made in partnership with the Getty Museum, showing how to work with Linked Art, a linked open data model for cultural heritage objects. The Observable JavaScript tutorials demonstrate how to analyze artworks in Getty’s Online Collections.

A screenshot of the third Linked Art tutorial, showing a scatterplot of works by artist and nationality.

Bibliographia. An interactive plot of 50,000+ printed books from the sixteenth and seventeenth centuries, using LDA topic models and LargeVis to cluster similar texts. Made in D3.js and Canvas for the EarlyPrint project.

A screenshot of EarlyPrint site, showing the clusters of texts in LargeVis.