Swipytics: Leveraging Short-form Video Stream Metaphor in Exploratory Data Analysis
Authors
Jiwon Choi (Match Group), Sehi L'Yi (Harvard Medical School), Seojin Kim (North Carolina State University), Jaemin Jo (Sungkyunkwan University)
Presentation
- Session
- Lost in Dimensions
- Time
- Thursday, Nov 12, 15:09 – 15:18 (US/Eastern) · session 15:00 – 16:30
- Location
- Hall Essex north
Keywords
Visualization, Exploratory Data Analysis
Abstract
We present Swipytics, a mobile interface designed to lower the onboarding barrier to exploratory data analysis (EDA) by leveraging the metaphor of short-form video streams. While EDA tools are increasingly accessible to a broad and diverse audience, they often require users to first learn the interface through verbal instructions or lengthy video tutorials, leaving an onboarding barrier. To lower this barrier, we leverage the metaphor of short-form video streams, offering minimal and familiar user interactions for EDA, such as swipe gestures for exploring new visualizations, with visualizations recommended one at a time in a linear, user-controlled sequence. Our user study demonstrates that participants quickly achieved high levels of proficiency and confidence in EDA after a short self-learning period (approximately 100 seconds on average).
For Practitioners
This paper would interest practitioners who design or use data analysis tools, such as visualization researchers, data scientists, UX designers, mobile app developers, and analysts working with non-expert users. Practitioners could apply the paper’s insights by using familiar mobile interaction patterns, such as swipe-based short-form video streams, to make exploratory data analysis easier to learn and start. They could also design tools that present visualizations one at a time and recommend next views based on user interaction history.