A classification of infographics

Helen C. Purchase, Katherine Isaacs, Thomas Bueti, Ben Hastings, Aadam Kassam, Allen Kim, Steffan van Hoesen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Classifications are useful for describing existing phenomena and guiding further investigation. Several classifications of diagrams have been proposed, typically based on analytical rather than empirical methodologies. A notable exception is the work of Lohse and his colleagues, published in Communications of the ACM in December 1994. The classification of diagrams that Lohse proposed was derived from bottom-up grouping data collected from sixteen participants and based on 60 diagrams. Mean values on ten Likert-scales were used to predict diagram class. We follow a similar methodology to Lohse, using real-world infographics (i.e. embellished data charts) as our stimuli. We propose a structural classification of infographics, and determine whether infographics class can be predicted from values on Likert scales.

Original languageEnglish (US)
Title of host publicationDiagrammatic Representation and Inference - 10th International Conference, Diagrams 2018, Proceedings
EditorsGem Stapleton, Francesco Bellucci, Amirouche Moktefi, Peter Chapman, Sarah Perez-Kriz
PublisherSpringer-Verlag
Pages210-218
Number of pages9
ISBN (Print)9783319913759
DOIs
StatePublished - 2018
Event10th International Conference on the Theory and Application of Diagrams, Diagrams 2018 - Edinburgh, United Kingdom
Duration: Jun 18 2018Jun 22 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10871 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on the Theory and Application of Diagrams, Diagrams 2018
CountryUnited Kingdom
CityEdinburgh
Period6/18/186/22/18

Keywords

  • Classification
  • Empirical studies
  • Infographics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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