THESIS
2019
xiv, 125 pages : illustrations (some color) ; 30 cm
Abstract
As visuals are widely adopted to encode data and convey information, an increasing number
of researchers have focused on a new research problem, namely the investigation on
persuasive power in data visualizations. It is important for both visualization researchers
and practitioners to understand this persuasive power as it encompasses how visualizations
will influence human perceptions and behaviors. In this thesis, we contribute three
work to investigate how and to what extend we could design visualizations to be more
persuasive. Following a framework from persuasive technologies, we not only investigate
the persuasiveness of visualizations when they are adopted as the persuasive medium
(two empirical studies), but also provide an example of using visualizations as the persuasi...[
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As visuals are widely adopted to encode data and convey information, an increasing number
of researchers have focused on a new research problem, namely the investigation on
persuasive power in data visualizations. It is important for both visualization researchers
and practitioners to understand this persuasive power as it encompasses how visualizations
will influence human perceptions and behaviors. In this thesis, we contribute three
work to investigate how and to what extend we could design visualizations to be more
persuasive. Following a framework from persuasive technologies, we not only investigate
the persuasiveness of visualizations when they are adopted as the persuasive medium
(two empirical studies), but also provide an example of using visualizations as the persuasive
tool and social actor (an application work).
In the first work, we contribute a novel persuasive contextual factor: neighborhood
effects in bar charts. Results show that such neighborhood effects exist: a target bar surrounded
by high neighbor bars, is perceived to be lower as the same bar surrounded with
low neighbors. Yet, the effect size of this neighborhood effect is small compared to other
data-inherent effects.
In the second work, we conduct an empirical study to compare the persuasiveness of
different visual representations including charts and non-charts under a two-level comparison
task. We contribute six experiments with 1160 online crowdsourcing participants
recruited. Results show that non-chart representations are more persuasive than charts in
our experimental settings.
In the third work, we design a persuasive system to help improve the intergenerational
communications between the elderly and their children. We embed visualizations in an
asynchronous communication system to both encode the communication data and serve
as the visual feedbacks on user performances.
As this research area is in its infancy, we provide a more holistic view of how we design
and evaluate persuasive factors, encodings and systems.
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