Model and MEtadata Visualization

This white paper summarizes our research to date on TOME: Interactive TOpic Model and MEtadata Visualization, a tool designed to support the exploratory thematic analysis of digitized archival collections, funded through an NEH Office of Digital Humanities Startup Grant (201315). Thus far, the primary outcome of TOME is a set of visualizations intended to facilitate the interpretation of the topic model and its incorporation into extant humanities research practices. In contrast to other topic model browsers, which present the model on its own terms, TOME is informed by the process of conducting early-stage humanities research. In this way, our research also demonstrates the conceptual conversions--in terms of both design and process—that interdisciplinary collaboration necessarily entails. In making these conversions explicit, and exploring the implications of their successes and failures, we take up the call, as voiced by Johanna Drucker (2011), to resist the “intellectual Trojan horse” of visualization. We seek to model a new mode of interdisciplinary inquiry, one that brings the methodological emphasis of the digital humanities to bear on the practices of humanities research and computer science alike. Introduction and Overview William Lloyd Garrison, the nineteenth-century abolitionist, was widely renowned for his writing. The lines that began the first issue of his anti-slavery newspaper, The Liberator, in 1831, “I will not equivocate -I will not excuse -I will not retreat a single inch -AND I WILL BE HEARD," quickly became the rallying cry of the abolitionist movement in the United States. But one decade later, with several additional newspapers under his editorial control, Garrison decided to hire a woman, Lydia Maria Child, to edit the National Anti-Slavery Standard, the official newspaper of the American Anti-Slavery Society. Child was most famous as a novelist, but she also wrote stories for children and had published a bestselling cookbook. Garrison hoped that Child could bolster female support the cause, “impart[ing] useful hints to the government as well as to the family circle” (Karcher 1994). But did she? And if so, how effective—or how widely adopted—was this change in topic or tone? Questions like these, about the evolution of issues and ideas, prompted our work on the TOME project, which we describe in this white paper. TOME, short for Interactive TOpic Modeling and MEtadata Visualization, is a tool designed to support the exploratory thematic analysis of digitized archival collections. Muralidharan and Hearst (2012) have proposed that we think of the exploratory phase of humanities research as a process of sensemaking, one in which scholars aggregate concrete pieces of evidence into more abstract theoretical models. Their work on the WordSeer project draws upon the concept of Exploratory Data Analysis (EDA), which has played a role in quantitative research since the 1970s (Tukey 1977). In comparison to formal hypothesis testing, EDA is intended to help the researcher develop a general sense of the properties of the dataset before embarking on more specific inquiries. Typically, EDA combines