We are building an interactive, visual text analysis tool that aids users in analyzing a large collection of text. Unlike existing work in text analysis, which focuses either on developing sophisticated text analytic techniques or inventing novel visualization metaphors, ours is tightly integrating state-of-the-art text analytics with interactive visualization to maximize the value of both. In this paper, we focus on describing our work from two aspects. First, we present the design and development of a time-based, visual text summary that effectively conveys complex text summarization results produced by the Latent Dirichlet Allocation (LDA) model. Second, we describe a set of rich interaction tools that allow users to work with a created visual text summary to further interpret the summarization results in context and examine the text collection from multiple perspectives. As a result, our work offers two unique contributions. First, we provide an effective visual metaphor that tran...
Shixia Liu, Michelle X. Zhou, Shimei Pan, Weihong