Paper Machines is a plugin for the Zotero bibliographic management software that makes cutting-edge topic-modeling analysis in Computer Science accessible to humanities researchers without requiring extensive computational resources or technical knowledge. It synthesizes several approaches to visualization within a highly accessible user interface.
This project is a collaboration between historian Jo Guldi and ethnomusicologist Chris Johnson-Roberson, graciously supported by Google Summer of Code, the William F. Milton Fund, and the metaLAB @ Harvard.
It is designed to help scholars parse through large sets of information, capitalizing on current work in computer science, topic modeling, and visualization to generate iterative, time-dependent visualizations of what a hand-curated body of texts talks about and how it changes over time.
At a conceptual level, we believe that this tool will be a powerful resource in examining large quantities of information and allowing knowledge seekers to consider a broader, richer, often-ignored corpus of text. In doing so, we hope to enlist the power of digital humanities to tame the pile of paper, and redistribute the power that “official” paper took away.