How Do Captions Affect Visualization Reading?
May 03, 2022 Β· Declared Dead Β· π arXiv.org
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Authors
Hanxiu 'Hazel' Zhu, Shelly Shiying Cheng, Eugene Wu
arXiv ID
2205.01263
Category
cs.HC: Human-Computer Interaction
Citations
6
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Captions help readers better understand visualizations. However, if the visualization is intended to communicate specific features, should the caption be statistical, and focus on specific values, or perceptual, and focus on general patterns? Prior work has shown that when captions mention visually salient features, readers tend to recall those features. Still, we lack explicit guidelines for how to compose the appropriate caption. Further, what if the author wishes to emphasize a less salient feature? In this paper, we study how the visual salience of the feature described in a caption, and the semantic level of the caption description, affect a reader's takeaways from line charts. For each single- or multi-line chart, we generate 4 captions that 1) describe either the primary or secondary salient feature in a chart, and 2) describe the feature either at the statistical or perceptual levels. We then show participants random chart-caption pairs and record their takeaways. We find that the primary salient feature is more memorable for single-line charts when the caption is expressed at the statistical level; for primary and secondary features in multi-line charts, the perceptual level is more memorable. We also find that many readers will tend to recall y-axis numerical values when a caption is present.
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