Open AccessReading Thomas Jefferson with TopicViz: Towards a Thematic Method for Exploring Large Cultural Archives
Author(s) -
Lauren F. Klein,
Jacob Eisenstein
Publication year - 2013
Publication title -
scholarly and research communication
Language(s) - English
Resource type - Journals
ISSN - 1923-0702
DOI - 10.22230/src.2013v4n3a121
Subject(s) - computer science , digitization , workflow , reading (process) , data science , world wide web , cultural heritage , visualization , epic , thematic map , software , database , history , artificial intelligence , linguistics , programming language , literature , art , philosophy , cartography , archaeology , computer vision , geography
In spite of what Ed Folsom has called the “epic transformation of archives,” referring to the shift from print to digital archival form, methods for exploring these digitized collections remain underdeveloped. One method prompted by digitization is the application of automated text mining techniques such as topic modeling -- a computational method for identifying the themes that recur across an archive of documents. We review the nascent literature on topic modeling of literary archives, and present a case study, applying a topic model to the Papers of Thomas Jefferson. The lessons from this work suggest that the way forward is to provide scholars with more holistic support for visualization and exploration of topic model output, while integrating topic models with more traditional workflows oriented around assembling and refining sets of relevant documents. We describe our ongoing effort to develop a novel software system that implements these ideas.