Tropes and Tribulations: Exploring Computational Text Analysis with the Data-Sitters Club
Lee Skallerup Bessette | Georgetown University; Katia Bowers | University of British Columbia; Maria Cecire | Bard College; Quinn Dombrowski | Stanford University; Anouk Lang | University of Edinburgh; Roopika Risam | Salem State University
March 11, 2021 | 3:00 PM CST
Within the broad, interdisciplinary field of digital humanities, scholars have been using computational methods to answer new questions — and refine answers to old questions — for decades. While these methods have seen prominent uptake in English Literature and History departments in the United States, their impact has been more limited in other fields, including Children’s Literature and Literatures other than English. The Data-Sitters Club is a team of scholars whose own work spans a wide range of topics, from Anglo-American children’s literature, to postcolonial studies, to comparative and non-English literatures, to digital humanities infrastructure. Brought together by their shared passion for Ann M. Martin’s series “The Baby-Sitters Club” (1986-2000, and recently revitalized by a graphic novel series and Netflix show), and supported by the Stanford Literary Lab, the “data-sitters” have applied many different text analysis methods — including TEI, text reuse algorithms, and natural-language processing for multiple languages — to the Baby-Sitters Club corpus, and written up the process in a conversational, accessible way on their website, in order to support scholars who are new to these methods. In this talk, the data-sitters will reflect on the value of public-oriented feminist collaboration: what’s worked, what’s failed, what kinds of questions they’ve come closer to answering. They will also share advice for other scholars interested in undertaking collaborative DH work.