  As data visualizations have been increasingly applied in mass communication,
designers often seek to grasp viewers immediately and motivate them to read
more. Such goals, as suggested by previous research, are closely associated
with the activation of emotion, namely affective arousal. Given this
motivation, this work takes initial steps toward understanding the
arousal-related factors in data visualization design. We collected a corpus of
265 data visualizations and conducted a crowdsourcing study with 184
participants during which the participants were asked to rate the affective
arousal elicited by data visualization design (all texts were blurred to
exclude the influence of semantics) and provide their reasons. Based on the
collected data, first, we identified a set of arousal-related design features
by analyzing user comments qualitatively. Then, we mapped these features to
computable variables and constructed regression models to infer which features
are significant contributors to affective arousal quantitatively. Through this
exploratory study, we finally identified four design features (e.g.,
colorfulness, the number of different visual channels) cross-validated as
important features correlated with affective arousal.

Human-Computer Interaction