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Termite: Visualization Techniques for Assessing Textual Topic Models

Jason Chuang, Christopher D. Manning, Jeffrey Heer. Advanced Visual Interfaces, 2012
Figure for Termite: Visualization Techniques for  Assessing Textual Topic Models
The Termite system. A tabular view (left) displays term-topic distributions for an LDA topic model. A bar chart (right) shows the marginal probability of each term.
Materials
Abstract
Topic models aid analysis of text corpora by identifying latent topics based on co-occurring words. Real-world deployments of topic models, however, often require intensive expert verification and model refinement. In this paper we present Termite, a visual analysis tool for assessing topic model quality. Termite uses a tabular layout to promote comparison of terms both within and across latent topics. We contribute a novel saliency measure for selecting relevant terms and a seriation algorithm that both reveals clustering structure and promotes the legibility of related terms. In a series of examples, we demonstrate how Termite allows analysts to identify coherent and significant themes.
BibTeX
@inproceedings{2012-termite,
  title = {Termite: Visualization Techniques for  Assessing Textual Topic Models},
  author = {Chuang, Jason AND Manning, Christopher AND Heer, Jeffrey},
  booktitle = {Advanced Visual Interfaces},
  year = {2012},
  url = {https://idl.uw.edu/papers/termite},
  doi = {10.1145/2254556.2254572}
}