TopicViz: interactive topic exploration in document collections

Authors:
Jacob Eisenstein;Duen Horng Chau;Aniket Kittur;Eric Xing
Affiliations:
Georgia Institute of Technology, Atlanta, Georgia, USA;Carnegie Mellon University, Pittsburgh, Pennsylvania, USA;Carnegie Mellon University, Pittsburgh, Pennsylvania, USA;Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
Venue:
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Year:
2012

Citing 11
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Abstract

Existing methods for searching and exploring large document collections focus on surface-level matches to user queries, ignoring higher-level semantic structure. In this paper we show how topic modeling - a technique for identifying latent themes across a large collection of documents - can support semantic exploration. We present TopicViz: an interactive environment which combines traditional search and citation-graph exploration with a force-directed layout that links documents to the latent themes discovered by the topic model. We describe usage scenarios in which TopicViz supports rapid sensemaking on large document collections.