Which emphasis technique to use? Perception of emphasis techniques with varying distractors, backgrounds, and visualization types

Abstract

Emphasis effects are visual changes that make data elements distinct from their surroundings. Designers may use computational saliency models to predict how a viewer’s attention will be guided by a specific effect; however, although saliency models provide a foundational understanding of emphasis perception, they only cover specific visual effects in abstract conditions. To address these limitations, we carried out crowdsourced studies that evaluate emphasis perception in a wider range of conditions than previously studied. We varied effect magnitude, distractor number and type, background, and visualization type, and measured the perceived emphasis of 12 visual effects. Our results show that there are perceptual commonalities of emphasis across a wide range of environments, but also that there are limitations on perceptibility for some effects, dependent on a visualization’s background or type. We developed a model of emphasis predictability based on simple scatterplots that can be extended to other viewing conditions. Our studies provide designers with new understanding of how viewers experience emphasis in realistic visualization settings.

When reality backfires: Product evaluation context and the effectiveness of augmented reality in e‐commerce

“…Taylor et al, 1979). Certain elements of a stimulus may become perceptually less salient if they are visually less prominent to the viewer than other elements of the stimulus (Borgida & Howard-Pitney, 1983;Hall et al, 2016;Mairena et al, 2022).…”

“…The salience of situational stimuli was found to influence viewers' perceptions and judgments in an automatic, subconscious way (McArthur & Post, 1977; Nisbett & Ross, 1980; S. Taylor et al, 1979). Certain elements of a stimulus may become perceptually less salient if they are visually less prominent to the viewer than other elements of the stimulus (Borgida & Howard‐Pitney, 1983; Hall et al, 2016; Mairena et al, 2022).…”

“…For our manipulation of the context's perceptual salience, we created blurred copies of the two context stimuli resulting from the initial pretest described in Section 3. We decided to operationalize the reduction of the context's perceptual salience by blurring, as it is a common way to decrease the visual prominence of parts within a scene (Hall et al, 2016; Mairena et al, 2022).…”

Show and tell: approaches for effective figures

“…In addition, the choice of figure elements for data representation can bias figure interpretation. For instance, modifying shape size has been shown to be more effective than modifying color when attempting to visualize differences in magnitude (Mairena et al 2020). Finally, some elements can affect the perception of others when used in combination.…”

Light mode and dark mode: Which one is suitable when using public‐facing web maps? An experimental evaluation using eye‐tracking

“…In a bright lighting environment, in contrast, the pupil size changed less during the task in light mode than in dark mode. Mairena et al (2021) found that the dark mode scatterplot performed well with lower search times and higher accuracies than the light mode scatterplot.…”