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 language | English |
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Title of host publication | Diagrammatic Representation and Inference - 10th International Conference, Diagrams 2018 Edinburgh, UK, June 18–22, 2018 Proceedings |
Editors | Peter Chapman, Gem Stapleton, Amirouche Moktefi, Sarah Perez-Kriz, Francesco Bellucci |
Place of Publication | Cham Switzerland |
Publisher | Springer |
Pages | 210-218 |
Number of pages | 9 |
ISBN (Electronic) | 9783319913766 |
ISBN (Print) | 9783319913759 |
DOIs | |
Publication status | Published - 2018 |
Externally published | Yes |
Event | International Conference on the Theory and Application of Diagrams 2018 - Edinburgh, United Kingdom Duration: 18 Jun 2018 → 22 Jun 2018 Conference number: 10th https://link.springer.com/book/10.1007/978-3-319-91376-6 (Proceedings) http://www.diagrams-conference.org/2018/ (Website) |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer |
Volume | 10871 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | International Conference on the Theory and Application of Diagrams 2018 |
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Abbreviated title | Diagrams 2018 |
Country/Territory | United Kingdom |
City | Edinburgh |
Period | 18/06/18 → 22/06/18 |
Internet address |
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Keywords
- Classification
- Empirical studies
- Infographics