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The Biasing Effect of Word Length in Font Size Encodings

Eric Alexander, Chih-Ching Chang, Mariana Shimabukuro, Steve Franconeri, Christopher Collins, Michael Gleicher
IEEE Visualization Poster Proceedings — Oct 2016
    Download the publication : Text_Perception_Poster___InfoVis_2016.pdf [196Ko]  
    From word clouds to cartographic labels to word trees, many visualizations encode data within the sizes of fonts. While font size can be an intuitive dimension for the viewer, it may also bias the perception of the underlying values. Viewers might conflate the size of a word's font with a word's width, with the number of letters it contains, or with the larger or smaller heights of particular characters ('o' vs. 'p' vs. 'b'). In an ongoing set of experiments, we have found that such factors--which are irrelevant to the encoded values--can indeed influence comparative judgements of font size. For this poster, we present one such experiment showing the biasing effect of word length.

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    BibTex references

      author       = "Alexander, Eric and Chang, Chih-Ching and Shimabukuro, Mariana and Franconeri, Steve and Collins, Christopher and Gleicher, Michael",
      title        = "The Biasing Effect of Word Length in Font Size Encodings",
      booktitle    = "IEEE Visualization Poster Proceedings",
      month        = "Oct",
      year         = "2016",
      url          = "http://graphics.cs.wisc.edu/Papers/2016/ACSFCG16"

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