Kineticharts: Augmenting Affective Expressiveness of Charts in Data Stories with Animation Design

Xingyu Lan, Yang Shi, Yanqiu Wu, Xiaohan Jiao, Nan Cao

View presentation: 2021-10-29T13:15:00Z GMT-0600 Change your timezone on the schedule page
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We present Kinecticharts, an animation design scheme for creating affective charts in data stories. Kineticharts consist of two main dimensions: (i) five positive affects, including joy, amusement, surprise, tenderness, and excitement, and (ii) three charts, including bar charts, line charts, and pie charts. We also tagged Kineticharts with five types of editorial layer, including chart marks, chart axes, chart as a whole, embellishment, and camera to describe which objects in a chart have been animated to communicate affective messages. The full version of Kineticharts can be viewed at
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Data stories often seek to elicit affective feelings from viewers. However, how to design affective data stories remains under-explored. In this work, we investigate one specific design factor, animation, and present Kineticharts, an animation design scheme for creating charts that express five positive affects: joy, amusement, surprise, tenderness, and excitement. These five affects were found to be frequently communicated through animation in data stories. Regarding each affect, we designed varied kinetic motions represented by bar charts, line charts, and pie charts, resulting in 60 animated charts for the five affects. We designed Kineticharts by first conducting a need-finding study with professional practitioners from data journalism and then analyzing a corpus of affective motion graphics to identify salient kinetic patterns. We evaluated Kineticharts through two user studies. The results suggest that Kineticharts can accurately convey affects, and improve the expressiveness of data stories, as well as enhance user engagement without hindering data comprehension compared to the animation design from DataClips, an authoring tool for data videos.