As online news increasingly include data journalism, there is a corresponding increase in the incorporation of visualization in article thumbnail images. However, little research exists on the design rationale for visualization thumbnails, such as resizing, cropping, simplifying, and embellishing charts that appear within the body of the associated article. Therefore, in this paper we aim to understand these design choices and determine what makes a visualization thumbnail inviting and interpretable. To this end, we first survey visualization thumbnails collected online and discuss visualization thumbnail practices with data journalists and news graphics designers. Based on the survey and discussion results, we then define a design space for visualization thumbnails and conduct a user study with four types of visualization thumbnails derived from the design space. The study results indicate that different chart components play different roles in attracting reader attention and enhancing reader understandability of the visualization thumbnails. We also find various thumbnail design strategies for effectively combining the charts' components, such as a data summary with highlights and data labels, and a visual legend with text labels and Human Recognizable Objects (HROs), into thumbnails. Ultimately, we distill our findings into design implications that allow effective visualization thumbnail designs for data-rich news articles. Our work can thus be seen as a first step toward providing structured guidance on how to design compelling thumbnails for data stories.

We present Roslingifier, a data-driven storytelling method for animated scatterplots. Like its namesake, Hans Rosling (1948-2017), a professor of public health and a spellbinding public speaker, Roslingifier turns a sequence of entities changing over time-such as countries and continents with their demographic data-into an engaging narrative elling the story of the data. This data-driven storytelling method with an in-person presenter is a new genre of storytelling technique and has never been studied before. In this article, we aim to define a design space for this new genre-data presentation-and provide a semi-automated authoring tool for helping presenters create quality presentations. From an in-depth analysis of video clips of presentations using interactive visualizations, we derive three specific techniques to achieve this: natural language narratives, visual effects that highlight events, and temporal branching that changes playback time of the animation. Our implementation of the Roslingifier method is capable of identifying and clustering significant movements, automatically generating visual highlighting and a narrative for playback, and enabling the user to customize. From two user studies, we show that Roslingifier allows users to effectively create engaging data stories and the system features help both presenters and viewers find diverse insights.

As online marketplaces adopt new technologies to encourage consumers’ purchases (e.g., one-click purchases), the number of consumers who impulsively buy products also increases. Although some interventions have been introduced for consumers’ self-controlled purchases, there have been few studies that evaluate the effectiveness of the techniques in the real environment. In this paper, we conducted an online survey with 118 consumers in their 20s to investigate their impulse buying behaviors and self-control strategies. Based on the survey results and literature surveys, we developed interventions that can assist consumers in controlling their online purchase habits, including Reflection, Distraction, Desire Reduction, and Salient Cost. For evaluation, we enrolled 107 participants in a user study on a real-world e-commerce site. The results indicate that all interventions were effective in reducing impulse buying urges, with variations in user experiences. Our findings and design implications are discussed.

In spite of the evolution of Augmented Reality~(AR) technology, it is not wide spread in everyday life. There may be many reasons, but one of the reasons is that it has been developed for very specific users, such as researchers and professionals. To overcome this problem, Grubert et al. proposed the pervasive AR. It is not limited to a specific situation, but is usable in various instances and providing continuous and flexible AR experience. The AR browser is the example of utilizing pervasive AR. The AR browser understands the context of the user and provides corresponding information. However, if the corresponding information to the context of user cannot reach the user in time due to massive data transmission, unexpected network congestion, poor service quality or signal strength, it cannot be guaranteed to be continuous. This leads to a degradation of the user experience, and it cannot support pervasive AR. This paper presents the Progressive Augmented Reality, the way which quickly send incomplete, yet informative, response about the user's current context rather than wait for sending complete information to the user. The concept of Progressive Augmented Reality comes from Progressive Data Science. Our system is aware of network quality by collecting various network health parameters. According to the network status quality, it divides the chunk information to the optimal number and transmits the one that have the highest priority among the divided information. By conducting the above process iteratively, all the divided information is updated. Our client-side system utilizes Android ARCore and has been tested on Google Pixel 2XL.