Investigating the Effects of Mood & Usage Behaviour on Notification Response Time
Judith S. Heinisch, Nan Gao, Christoph Anderson, Shohreh Deldari,, Klaus David, Flora Salim

TL;DR
This study explores how users' mood and usage behavior influence notification response times on smartphones, demonstrating a personalized prediction model that could enhance notification management systems.
Contribution
It introduces a regression model that accurately predicts notification response times based on mood and physiological signals, highlighting personalized factors affecting response behavior.
Findings
Model achieved MAE of 0.7764 ms and RMSE of 1.0527 ms
Physiological signals from wristbands can indicate mood impacts
Individual differences significantly affect notification response times
Abstract
Notifications are one of the most prevailing mechanisms on smartphones and personal computers to convey timely and important information. Despite these benefits, smartphone notifications demand individuals' attention and can cause stress and frustration when delivered at inopportune timings. This paper investigates the effect of individuals' smartphone usage behavior and mood on notification response time. We conduct an in-the-wild study with more than 18 participants for five weeks. Extensive experiment results show that the proposed regression model is able to accurately predict the response time of smartphone notifications using current user's mood and physiological signals. We explored the effect of different features for each participant to choose the most important user-oriented features in order to to achieve a meaningful and personalised notification response prediction. On…
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Taxonomy
TopicsPersonal Information Management and User Behavior · Green IT and Sustainability · Impact of Technology on Adolescents
