Transparency to Visibility (T2V)

Abstract

Advances in network visualization technologies have the potential to humanistic inquiry devoted to better understanding the circulation of power and influence within cultural systems. While new technologies have made generating high-quality and even dynamic network visualizations relatively easy, key challenges remain for humanities researchers. Creative, historiographic, biographical, and similar artifacts are usually not easily transformed into the kinds of data structures necessary for network visualization. The Transparency to Visibility (T2V) Project was initiated to develop new methods and toolkits that can support humanistic researchers who need to transform unstructured textual datasets into data structures that support useful and informative network visualization. The T2V team used bioethics accountability statements to pilot and evaluate different methods for transforming and visualizing relational networks based on data in unstructured text. The resulting machine-learning-enhanced natural language processing (NLP) and metadata-assisted approaches offer promising potential pathways for contemporary digital humanities and future toolkit development.