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A Classification of Infographics

  • Helen C. PurchaseEmail author
  • Katherine Isaacs
  • Thomas Bueti
  • Ben Hastings
  • Aadam Kassam
  • Allen Kim
  • Steffan van Hoesen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10871)

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.

Keywords

Infographics Classification Empirical studies 

Notes

Acknowledgements

This research was conducted while the first author was visiting the University of Arizona. We are grateful to all the participants, and to Babak Saleh and Michelle Borkin who shared their image data sets. Ethical approval was given by the University of Arizona Institutional Review Board (ref: 1711982836).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Helen C. Purchase
    • 1
    Email author
  • Katherine Isaacs
    • 2
  • Thomas Bueti
    • 2
  • Ben Hastings
    • 2
  • Aadam Kassam
    • 2
  • Allen Kim
    • 2
  • Steffan van Hoesen
    • 2
  1. 1.School of Computing ScienceUniversity of GlasgowGlasgowUK
  2. 2.Department of Computer ScienceUniversity of ArizonaTucsonUSA

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