Folklorists, like most practitioners in a field, understand the history of their discipline through a combination of their own reading and the consensus inherited from their graduate training and professional interactions. Disciplinary history, an effectively oral form of communication, codifies quickly. Highly contingent and random processes become widely understood as historically inevitable. In this preliminary report on a larger project examining the application of computational methodologies in the service of intellectual history, we explore the use of topic modeling as a way to understand the ebb and flow of topics and paradigms within a domain. Using JSTOR’s Data for Research application programming interface to access the contents of 6,778 articles from three folklore studies journals (Journal of American Folklore, Western Folklore, Journal of Folklore Research), we used one form of topic modeling, Latent Dirichlet Allocation, to delineate 50 distinct topics drawn from 125 years of research publication. Of particular interest here was the legendary “turn toward performance” in our field.