DataHalo: A Customizable Notification Visualization System for Personalized and Longitudinal Interactions

要旨

People struggle with the overflow of smartphone notifications but often face two challenges: (1) prioritizing the informative notifications as they wish and (2) retaining the delivered information as long as they want to utilize it. In this paper, we present DataHalo, a customizable notification visualization system that represents notifications as prolonged ambient visualizations on the home screen. DataHalo supports keyword-based filtering and categorization, and draws graphical marks based on time-varying importance model to enable longitudinal interaction with the notifications. We evaluated DataHalo through a usability study ($N$ = 17), from which we improved the interface. We then conducted a three-week deployment study ($N$ = 12) to assess how people use DataHalo in their domestic contexts. Our study revealed that people generated various visualization settings for different kinds of apps. Drawing on both quantitative and qualitative findings, we discussed implications for supporting effective notification management through customizable ambient visualizations.

著者
Guhyun Han
Seoul National University, Seoul, Korea, Republic of
Jaehun Jung
University of Washington, Seattle, Washington, United States
Young-Ho Kim
NAVER AI Lab, Seongnam, Gyeonggi, Korea, Republic of
Jinwook Seo
Seoul National University, Seoul, Korea, Republic of
論文URL

https://doi.org/10.1145/3544548.3580828

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Smartphones and Notifications

Hall G2
6 件の発表
2023-04-26 01:35:00
2023-04-26 03:00:00