Intersectional feminist practices ground my work in cultural analytics. In Modern Sentimentalism, for example, I engage digital text analysis and data visualization alongside print-based archival practices to examine how US female novelists reinvented sentimentalism in the modernist era. Archival platforms, text-mining tools, and Ngrams help me to establish that scholarly conversations about sentimentalism as a modern literary aesthetic have not kept pace with sentiment’s cultural purchase in the twentieth century. I theorize why this disparity persists and demonstrate that feminine feeling, far from being peripheral to twentieth-century modernism, centrally shapes its principles and preoccupations.
Reassessments of gendered, racialized narratives of cognition and emotion equally motivate my work in computer-aided public humanities. With digital media scholars at Michigan State and Northwood University, I have recently completed a mixed methods study on gender identity and digital avatars as sentimental characters. This study appears in Games and Culture. Another piece, on the prehistory of the contemporary quantified self movement, appeared in Modernism/modernity’s online feature In These Times. An invited, co-edited cluster for Modernism/modernity’s Print+ platform, on “Modernism and Diagnosis,” is in its final stages.
My teaching also involves students in the use of digital tools to enhance textual analysis and to create socially-impactful projects. At Menlo, I am training a cohort of students in algorithmic media studies and ethnographic research as part of a program I have designed to examine (nearby) Silicon Valley contemporary culture. My essay on teaching quantitative methods to undergraduates appears in a forthcoming volume in the MLA Options for Teaching Series.