Visualizing the affective structure of a text document

  • Authors:

  • Hugo Liu;Ted Selker;Henry Lieberman

  • Affiliations:

  • MIT Media Lab, Cambridge, MA;MIT Media Lab, Cambridge, MA;MIT Media Lab, Cambridge, MA

  • Venue:
  • CHI '03 Extended Abstracts on Human Factors in Computing Systems
  • Year:
  • 2003

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Abstract

This paper introduces an approach for graphically visualizing the affective structure of a text document. A document is first affectively analyzed using a unique textual affect sensing engine, which leverages commonsense knowledge to classify text more reliably and comprehensively than can be achieved with keyword spotting methods alone. Using this engine, sentences are annotated using six basic Ekman emotions. Colors used to represent each of these emotions are sequenced into a color bar, which represents the progression of affect through a text document. Smoothing techniques allow the user to vary the granularity of the affective structure being displayed on the color bar. The bar is hyperlinked in a way such that it can be used to easily navigate the document. A user evaluation demonstrates that the proposed method for visualizing and navigating a document's affective structure facilitates a user's within-document information foraging activity.