skip to main content
10.1145/765891.765961acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
Article

Visualizing the affective structure of a text document

Published:05 April 2003Publication History

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.

References

  1. Liu, H., Lieberman, H., Selker, T. A Model of Textual Affect Sensing using Real-World Knowledge. To Appear in Proceedings of IUI 2003. Miami, Florida. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Valdez, P., & Mehrabian, A. Effects of color on emotions. Journal of Experimental Psychology: General, 123, 394--409. (1994).Google ScholarGoogle ScholarCross RefCross Ref
  1. Visualizing the affective structure of a text document

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      CHI EA '03: CHI '03 Extended Abstracts on Human Factors in Computing Systems
      April 2003
      471 pages
      ISBN:1581136374
      DOI:10.1145/765891

      Copyright © 2003 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 5 April 2003

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • Article

      Acceptance Rates

      Overall Acceptance Rate6,164of23,696submissions,26%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader