Let's Get Personal: Exploring the Design of Personalized Visualizations

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Beleicia Bullock, Shunan Guo, Eunyee Koh, Ryan Rossi, Fan Du, Jane Hoffswell

 View presentation:2022-10-20T14:00:00ZGMT-0600Change your timezone on the schedule page
2022-10-20T14:00:00Z

Exemplar figure, described by caption below — This heat map provides an overview of the articles in our personalized visualization corpus based on the (a) personalized attributes contained in the article, (b) granularity, and (c) resulting codes for different publications. We also break down the articles by publication. Attributes that only appeared in 1-3 articles are grouped together under “other.”

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The live footage of the talk, including the Q&A, can be viewed on the session page, Personal Visualization, Theory, Evaluation, and eXtended Reality.

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Keywords

Human-centered computing—Visualization—Visualization application domains

Abstract

Media outlets often publish visualizations that can be personalized based on users’ demographics, such as location, race, and age. However, the design of such personalized visualizations remains underexplored. In this work, we contribute a design space analysis of 47 public-facing articles with personalized visualizations to understand how designers structure content, encourage exploration, and present insights. We find that articles often lack explicit exploration suggestions or instructions, data notices, and personalized visual insights. We then outline three trajectories for future research: (1) explore how users choose to personalize visualizations, (2) examine how exploration suggestions and examples impact user interaction, and (3) investigate how personalization influences user insights.