A team of students will collaborate with a doctoral fellow in Computational Humanities and the Asian American Studies Librarian to develop a statistics-based Natural Language Processing toolkit to study the linguistic styles of Asian American short stories published between 1974 and 2024. This toolkit will support historians, literary scholars, and humanities researchers in general who wish to conduct computational or quantitative literary research. The toolkit will include an annotated code bank that handles textual data and Natural Language Processing, documentation of best practices in quantitative literary research, and case studies. The team will design and create this toolkit by combining a foundational understanding of this body of literature with Natural Language Processing techniques gained over the summer. The work of this team may result in the release of a major open-access program or software, research website, or publication.
Project Lead: Matthew Hayes (Duke University Libraries), Richard So (English), and Shen Chen (Visiting Scholar)and Jerry Zou (Computational Media and History)
Project Manager:
