Typeface size and weight and word location influence on relative size judgments in tag clouds. (February 2018)

• Record Type: Journal Article
• Authors: Dhou, Khaldoon; Hadzikadic, Mirsad; Faust, Mark
• Is Part Of: Journal of visual languages & computing. Volume 44(2018)
• Page Start: 97
• Page End: 105
• Publication Date: 2018-02
• Subjects: Tag clouds -- Perception -- Psychophysics -- Size judgment; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2017.11.009
• Languages: English
• ISSNs: 1045-926X

Abstract

Abstract: This paper focuses on viewers' perception of the relative size of words presented in tag clouds. Tag clouds are a type of visualization that displays the contents of a document as a cluster (cloud) of key words (tags) with frequency (importance) indicated by tag word features such as size or color, with variation of size within a tag cloud being the most common indicator of tag importance. Prior studies have shown that word size is the most influential factor of tag importance and tag memory. Systematic biases in relative size perception in tag clouds are therefore likely to have important implications for viewer understanding of tag cloud visualizations. Significant under- and over-perception of the relative size of tag words were observed, depending on the relative size ratio of the target tag words compared. The qualitative change in the direction of the estimation bias was predicted by a simple power-law model for size perception. This bias in relative size perception was modulated somewhat by a change to a bold typeface, but the typeface effect varied in a complex manner with the size and location of the tags. The results provide a first report of systematic biases in relative size judgment in tag clouds, suggest that, to a first approximation, simple power-law scaling models developed for simple displays containing 1–2 objects on a blank background, may be applicable to relative size judgments in complex tag clouds. The results may provide useful design guidance for tag cloud designers.