“Don’t Bother Me. I’m Socializing!”
A Breakpoint-Based Smartphone Notification System
Abstract
Smartphone notifications provide application-specific information in real-time, but could distract users from in-person social interactions when delivered at inopportune moments. We explore breakpoint-based notification management, in which the smartphone defers notifications until an opportune moment. With a video survey where participants selected appropriate moments for notifications from a video-recorded social interaction, we identify four breakpoint types: long silence, a user leaving the table, others using smartphones, and a user left alone. We introduce a Social Context-Aware smartphone Notification system, SCAN, that uses built-in sensors to detect social context and identifies breakpoints to defer smartphone notifications until a breakpoint. We conducted a controlled study with ten friend groups who had SCAN installed on their smartphones while dining at a restaurant. Results show that SCAN accurately detects breakpoints (precision=92.0%, recall=82.5%), and reduces notification interruptions by 54.1%. Most participants reported that SCAN helped them to focus better on in-person social interaction and found selected breakpoints appropriate.
Publications
“Don’t Bother Me. I’m Socializing!”: A Breakpoint-Based Smartphone Notification System
Chunjong Park, Junsung Lim, Juho Kim, Sung-Ju Lee, and Dongman Lee
Proceedings of ACM CSCW 2017, Portland, OR, February 2017.
PDF
Proceedings of ACM CSCW 2017, Portland, OR, February 2017.
People
Media
KAIST Breakthroughs KAIST Breakthroughs, 2017 Fall
"Phone learns to send app notifications only when you want them" NewScientist, 2017.03.23
Research Highlights KAIST SoC Annual Report, 2017.02.20