18. Gender Patterns in English-Language Fiction and Interrogating Data with Ted Underwood and David Bamman

This episode features Ted Underwood, a professor in the School of Information Sciences and Department of English at the University of Illinois Urbana-Champaign, and David Bamman, an associate professor at UC Berkeley’s School of Information. We discuss their 2018 Cultural Analytics paper co-authored with literary studies PhD student Sabrina Lee, titled “The Transformation of Gender in English-Language Fiction.” We trace how Twitter brought Ted and David together as collaborators, and the email that sparked the beginnings of this project. They describe how this paper uses predictive modeling for an unconventional purpose, and various “means of interrogating data.” They also provide tips for establishing collaborative relationships, and advocate using substantive research questions to motivate learning technical skills.

Om Podcasten

Large-scale data has become a major component of research about human behavior and society. But how are interdisciplinary collaborations that use large-scale social data formed and maintained? What obstacles are encountered on the journey from idea conception to publication? In this podcast, we investigate these questions by probing the “research diaries” of scholars in computational social science and adjacent fields. We unmask the research process with the hope of normalizing the challenges of and increasing accessibility in academia. Music: Jon Gillick.