Thumbnails for Data Stories: What Makes Visualization Thumbnails Inviting and Interpretable?

Abstract

When people browse online news, small thumbnail images accompanying links to articles attract their attention and help them to decide which articles to read. As an increasing proportion of online news can be construed as data journalism, we have witnessed a corresponding increase in the incorporation of visualization in article thumbnails. However, there is little research to support alternative design choices for visualization thumbnails, which include resizing, cropping, simplifying, and embellishing charts appearing within the body of the associated article. We therefore sought to better understand these design choices and determine what makes a visualization thumbnail inviting and interpretable. This work presents our findings from a user study, from a survey of visualization thumbnails collected online, and from conversations with data journalists and news graphics designers. In the thesis, we define a design space for visualization thumbnails and conduct a user study to investigate what readers expect to see on the visualization thumbnail. The study results indicate different chart components play different roles in attracting readers’ attention and enhancing understandability of the readers on the visualization thumbnails. We also find various thumbnail design strategies by effectively combining the chart components, such as a data summary with highlights and data labels, and a visual legend with text labels and HROs. Ultimately, we distill our findings into design implications which allow effective visualization thumbnails for data-rich news articles. Our work can thus be seen as a first step toward providing structured guidance on how to design thumbnails for data stories.