Dissertation/Thesis Abstract

Measuring the effects of chart embellishments to better understand our perception of charts
by Skau, Drew West, Ph.D., The University of North Carolina at Charlotte, 2016, 100; 10245402
Abstract (Summary)

News organizations, non-profits, and even government agencies use information graphics to advertise and communicate their messages. Data visualizations are used heavily in these graphics, but they also often incorporate unusual design elements to help catch viewers’ eyes. In the struggle to rise to the top of the crowd, the data visualizations in infographics are often embellished with additions and modifications to the raw chart. The general consensus is that these embellishments can make charts less effective at communicating information, but most of them have never been tested to see if this is true. This work examines the factors in bar, pie, and donut charts that affect our perception of the charts.

I approach this in two different ways, both using a series of surveys on Mechanical Turk. The work on pie charts examines the individual contribution of arc-length, angle, and area variables so that embellishments may be evaluated based on their use of visual variables. The bar chart work examines some of the most common embellishments designers make to bar charts. This approach allows the isolated study of embellishments to determine which hinder or contribute the most to our perception of charts. I conclude with concrete recommendations based on the findings of the studies. My results show that conventional wisdom about how these charts are perceived is not always correct, and some types of embellishments are harmful while others have virtually no effect.

Indexing (document details)
Advisor: Kosara, Robert
Commitee: Beorkrem, Christopher, Dou, Wenwen, Latulipe, Celine, Wartell, Zachary
School: The University of North Carolina at Charlotte
Department: Computer Science
School Location: United States -- North Carolina
Source: DAI-B 78/05(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Cognitive psychology, Computer science
Keywords: Bar chart, Charts, Data visualization, Donut chart, Perception, Pie chart
Publication Number: 10245402
ISBN: 9781369454949
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