The development of a web-based tool for the visual exploration of the themes that recur across an archive, based on the text-analysis technique of topic modeling combined with the archive's related metadata. A digitized archive of 19th-century abolitionist newspapers would serve as the initial test case.
As archives are being digitized at an increasing rate, scholars will require new tools to make sense of this expanding amount of material. We propose to build TOME, a tool to support the interactive exploration and visualization of text-based archives. Drawing upon the technique of topic modeling--a computational method for identifying themes that recur across a collection--TOME will visualize the topics that characterize each archive, as well as the relationships between specific topics and related metadata, such as publication date. An archive of 19th-century antislavery newspapers, characterized by diverse authors and shifting political alliances, will serve as our initial dataset; it promises to motivate new methods for visualizing topic models and extending their impact. In turn, by applying our new methods to these texts, we will illuminate how issues of gender and racial identity affect the development of political ideology in the nineteenth century, and into the present day.