Computational Approaches to Oral History: Exploring the Densho Digital Repository

Abstract

Oral history collections often contain hundreds—if not thousands—of lengthy interviews. How can computational tools help researchers explore and analyze oral history collections? I apply two topic modeling techniques, BERTopic and Latent Dirichlet Allocation, to address research questions about the Densho Digital Repository, which documents Japanese American incarceration during World War II. I demonstrate how these tools can illuminate connections between ideas, facilitate comparison of interviews, and offer new ways to navigate the collection.