In the thesis, we define a space for designing visualization thumbnails and conduct a user study to investigate what readers expect to see on a visualization thumbnail. The results of the study show that different chart components play different roles in attracting readers' attention and improving reader comprehensibility on visualization thumbnails. Ultimately, we translate our findings into design implications that enable effective thumbnail visualization for data-rich news articles.
Finally, we summarize our findings in design implications for efficient thumbnail visualization for data-rich news articles (Section VI).
Designing Thumbnails
Storytelling in Thumbnails
Visualization in Data Journalism
To our knowledge, previous research has yet to examine the design of thumbnails in data journalism and specifically what we refer to as visualization thumbnails. To better understand current practices in designing visualization photos, we collected examples from data journalism media and spoke with news graphic designers.
A Survey of Visualization Thumbnails
Added components include explanatory text (or ex. text), highlights (e.g. the vertical arrow in Figure 1, the red bar in this thumbnail [https://econ.st/2ZhL5os], Human Recognizable Objects (HROs) [ 32 ), and Graphics Not Relevant to Data (GNRD) to capture all forms of graphic embellishment. HROs are image components used in legends (e.g. the Apple and Microsoft logos in Figure 1 and a small human object in this thumbnail – https://bit.ly/2YenA2V or to encode data points [41]. GNRDs are images or illustrations that reflect the article's context but are not directly related to the data, such as the blue image (bottom right) in this thumbnail https://bit.ly/2YenA2V.
Thumbnails for line charts (30 out of 67) tend to omit the X-axis title, the Y-axis, and legends. Other charts, including bar charts and scatter charts, tend to include varied combinations of components that are omitted or added in thumbnails. For example, FiveThirtyEight tends to remove almost all components of line charts in thumbnails; they also tend to add GNRDs and HROs (eg https://53eig.ht/330iOEW).
Meanwhile, traditional print media organizations like The New York Times and The Economist tend to crop or resize graphics when producing thumbnails. Finally, we see considerable variability in Table 1, which is an indication of the need for a greater understanding of how visualization tableau design choices affect reader interpretation, as well as the likelihood of readers to read the article. The trends discussed in this section are examples from the tables, but are by no means comprehensive.
Conversations with News Graphics Designers
Based on the results of the survey and our conversations, in this paper we consider avisualization thumbnail as a thumbnail that provides an overview of an article through visualizations to invite readers to click on the thumbnail for further reading. There are two perspectives on this definition, and each perspective leads to different goals for designing visualization thumbnails. From the perspective of a professional designer whose ultimate goal is to draw readers' attention to thumbnails and increase clicks on thumbnails, the goals of visualization thumbnails are not much different from the goals of non-visualization thumbnails.
Therefore, conventional design goals can work for evaluating visualization thumbnails, such as determining its attractiveness [21] or visual aesthetics [2-4]. Rather, the most important criteria for thumbnail design might include creating a visualization table that would allow readers to accurately and quickly judge whether the thumbnail article meets their criteria. While some goals of producers and consumers may compete with each other (e.g., visualizing a full story can be completed without clicks vs. providing little information about the story can make readers feel cheated) , we think there is a trade-off in which visualization thumbnails not only successfully invite consumers to the thumbnail-driven article, but also contribute to increased thumbnail clicks.
Although our conversations with practitioners were informal and by no means exhaustive, we were encouraged to learn about the lack of consensus regarding guidelines or patterns for designing thumbnails for visualizations. To investigate readers' preference for miniature designs for visualization, we formulate two research questions; (RQ1) which design types would readers most prefer and why?; (RQ2) which diagram components make readers prefer a visualization thumbnail. We use the generated thumbnails to recruit online participants and ask them to click on the thumbnail they prefer (section 4.3).
Visualization Thumbnail Design
The design variables include colorful backgrounds (e.g. http://bitly.kr/bumu2zoxf42), unique layouts (e.g. hiding map areas by a figure http://bitly.kr/Uxl0S2QfKan) and facial images with stimulating facial expressions and gestures (e.g. a photo of Trump http://bitly.kr/c81Jxnb0HNh). The chart of this type usually contains many components, including basic chart components such as axis labels, implicit legend, and a chart title as many other thumbnails do (for example, http://bitly.kr/4zHqPxFZWZ8). There are differences in axis representations (e.g. tick marks) and the use of gridlines in the original visualizations in the articles.
GNRDs are included in thumbnails to invite readers and stimulate their curiosity (eg the photo of a walking woman in this thumbnail http://bitly.kr/Pt2I9Mc0rFe). This type of thumbnail is often featured in FiveThirtyEight (eg http://bitly.kr/Uxl0S2QfKan) and Wall Street Journal Graphics. The main feature of C-type thumbnails is the use of a highlight block (eg the red blocks in Figure 2 C) to highlight a part of the visualization, as shown in this thumbnail - http://bitly.
Data labels are included in visualization thumbnails to highlight a specific part of the data that conveys the main point of the article (for example, '46.0%' and '39.8%' from this thumbnail http://bitly.kr/ 9ZFptkLoPWm In addition to the bars for highlighting, a reference line with data labels can also be used, replacing the role of information on the entire axis (for example, the vertical dotted line and numbers in this thumbnail, respectively http://bitly.kr/9ZFptkLoPWm) The main feature of the thumbnails in this type is that both logos and icons (for example icons of handcuffs in this thumbnail http://bitly.kr/4lVWOrYlbSm) refer directly to the data in the visualization.
A Workshop with Practitioners
Type D thumbnails have recognizable objects, such as logos or icons on a plain line graph with grid lines as a background. To summarize, we confirmed that the thumbnails can be used in the user study, and revised them based on the collected design suggestions (eg font size). We also found that the thumbnails produced are similar to what the practitioners make every day. In addition, the practitioners are also curious about readers' evaluation with the four types of thumbnails.
Study Procedure
We first perform statistical tests to find the type of thumbnail and readers' choice reasons (RQ1). We then conduct a component-wise qualitative analysis, focusing on graph components' roles and influences on reader clicks (RQ2).
Readers’ Preference for Thumbnail Types (RQ1)
When codifying topics, we classify topics into two categories, “inviting” and “interpretable,” which are the two main goals of thumbnail visualizations (subsection 3.2). In the interpretable category, we include topics related to delivering article content to readers. As a result, we have 43 comments for type A, 52 comments for type B, 89 comments for type C, and 77 comments for type D, with each participant reporting an average of 1.6 reasons for choice.
For example, we find that 60% of the 52 comments in the Type B table say that Type B thumbnails are inviting, and 29% of the comments describe that Type C thumbnails are considered interesting and eye-catching thumbnails. The fluctuations of the graph make me wonder why the data is the way it is and what the article can say about it." (P4). It's the only graphic that seems to tell a story right out of the gate - at least one that I could begin to make sense of." (p13).
Readers vote for Type A and Type C thumbnails as informative, interesting and predictable, but choose the highlights in Type C as the main difference and source of "curiosity stimulation". Reviewing all the results of the analysis, we find that readers prefer Type C and Type D Thumbnails over Type A and Type B Thumbnails. The low preference for Type B Thumbnails is somewhat unexpected, as performers rate them highly over Type B Thumbnails for their ability to effectively convey the main idea of an article. without causing much visual clutter (subsection 4.2). However, we believe that the result in this experiment suggests that the ability can be a double-edged sword, as it leads to low informativeness of thumbnails compared to other thumbnails, as pointed out by readers.
Role of Chart Components (RQ2)
GNRDs are fooled by visualization thumbnails by having two participants (P31, P35) imagine the context of the article. Pirolli, “Using Thumbnails for Web Search,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Baudisch, “Summary Thumbnails: Readable Reviews for Small Screen Web Browsers,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.
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