This poster describes visualization tools to support statistical literary analysis. Our observation of scholars’ work shows the importance of connecting the large-scale statistical analysis of texts with close reading of the text. To support this work, we have designed a system that integrates a corpus-wide overview of text-properties with a viewer for examining specific passages. The corpus viewer is designed to help identify “important” features in a text; the text viewer provides a focus+context view for examining the passages containing those features. These tools, in concert, allow one to observe a corpus wide pattern of tags and then propose a causal explanation for this pattern using the techniques of passage analysis.

@InProceedings{CG10,
  author       = "Correll, Michael and Gleicher, Michael",
  title        = "Poster: Understanding Tagged Text",
  booktitle    = "IEEE Information Visualization Conference Poster Proceedings",
  year         = "2010",
  url          = "http://graphics.cs.wisc.edu/Papers/2010/CG10"
}