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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.

AbstractThis study examined (a) what message variations characterize news articles that fact-check (mis)information (N = 914) and (b) how those message features shape audience engagement with the articles. The study content-analyzed fact-checking coverage from major news outlets in South Korea using both manual and computerized coding, focusing on three categories of message characteristics: source transparency, contextual information, and vividness. The content-analysis data were examined in relation to behavioral data of audience engagement (“like” and “angry” reactions, shares, and comments) on Naver News, the most popular news portal in South Korea. Using statistics and official reports as evidence and specifying when the claim at hand was made facilitated audience engagement behaviors. News articles triggered more audience comments when they (a) mentioned the importance of fact-checking the claim under scrutiny, and (b) conveyed negative content. Findings are discussed in light of the empirical and practical implications of the current efforts to fight “fake news” by news media.