Personal interactions and information access are happening more and more through the mediation of computing devices of various types all around us. In our daily life we use many computing devices running different versions of the same application such as email clients or social media platforms, which alert users about a new piece of information or event on all devices. In this paper we rst present a study investigating the factors influencing users' decisions in handling notications in a multi-device environment. We collected 57,242 in-the-wild notications from 24 users over a period of 21 days. We found that users' decisions in handling notications are impacted by their physical activity, location, network connectivity, application category and the device used for handling the previous notication. Finally, we show that an individualized model can predict the device on which the user will handle a notication in the given context with 82% specicity and 91% sensitivity.

NotifyMeHere: Intelligent Notification Delivery in Multi-Device Environments

Musolesi, M
2019

Abstract

Personal interactions and information access are happening more and more through the mediation of computing devices of various types all around us. In our daily life we use many computing devices running different versions of the same application such as email clients or social media platforms, which alert users about a new piece of information or event on all devices. In this paper we rst present a study investigating the factors influencing users' decisions in handling notications in a multi-device environment. We collected 57,242 in-the-wild notications from 24 users over a period of 21 days. We found that users' decisions in handling notications are impacted by their physical activity, location, network connectivity, application category and the device used for handling the previous notication. Finally, we show that an individualized model can predict the device on which the user will handle a notication in the given context with 82% specicity and 91% sensitivity.
Proceedings of the 2019 Conference on Human Information Interaction and Retrieval
103
111
Mehrotra, A and Hendley, R and Musolesi, M
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/735051
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