Publishing Empire: Modeling Early 20th-Century British Book Culture

What constituted British literature at the turn of the 20th century? What did the term mean to metropolitan readers after a century of unprecedented imperial expansion? This talk draws on industry-wide publishing data to explore the output of London’s book business, emphasizing the influence of high-profile authors from colonized nations on British print in the early 20th century. In particular, Anna Preus traces the groundbreaking publishing careers of Bengali authors Sarojini Naidu and Rabindranath Tagore, discussing how their successes in England shifted understandings of British literature, creating a version of the category that encompassed great works by writers from across the empire.

Anna Preus is an assistant professor in the English department at the University of Washington, where she studies and teaches 20th-century British and Anglophone literature and data science in the humanities. Her work has appeared or is forthcoming in ELH: English Literary History, Feminist Modernist Studies, Modernism/modernity Print Plus, EMNLP: Empirical Methods in Natural Language Processing, and the edited collection Expressive Networks: Poetry and Platform Cultures. She is involved in a number of collaborative digital projects, including The Paris Project, Responsible Datasets in Context, and the Cultural Analytics Research and Teaching Initiative, and her research has been supported by ACLS, the Mellon Foundation, and the Mozilla Foundation. At UW, Anna leads the Humanities Data Lab and serves as core faculty in the Textual Studies program.

Throughout 2025–26, CDH will host six public talks by leading scholars in Cultural Analytics. Open to all, the series invites audiences to explore the histories, theories, and practices that shape the evolving intersection of AI and the humanities.

Since the release of ChatGPT, conversations about artificial intelligence (AI) have generated both excitement and concern across the humanities. Much of the debate has focused on political and ethical questions—bias, labor, environmental impact, and intellectual property—as well as the effects of large language models (LLMs) on teaching and learning. Yet one question remains underexplored: how might AI contribute directly to humanities scholarship?