Gabi Kirilloff uses digital methods to examine patterns and outliers in text-based corpora. Her work often combines computation and close reading to examine the relationship between gender and agency.
Kirilloff's book project, Keeping the Reader Close, employs computational analysis alongside close reading to examine reader address in a corpus of over 3,000 nineteenth- and twentieth-century Anglophone novels. To “distant read” these interjections, Kirilloff employs a computational method that separates dialogue from narration and detects address at scale. She uses the resulting data to argue that specific groups of writers (including female and African American authors) use address to subvert the conventional relationship between reader and text.
Kirilloff teaches classes on Women's Writing, digital methods, computational analysis, and video-games. She has worked on a number of large scale digital projects, including The William Blake Archive, The Walt Whitman Archive, and The Willa Cather Archive. While a graduate student at the University of Nebraska, Kirilloff served as the assistant manager for the Nebraska-Literary Lab, where she led an interdisciplinary team of faculty and students on a project that used machine learning to model gender stereotypes in 3,329 nineteenth-century novels. Her work has appeared in journals including College Literature, Digital Scholarship in the Humanities, and Cultural Analytics.