Title: Large-scale evaluation of call-availability prediction
Abstract: We contribute evidence to which extent sensor- and contextual information available on mobile phones allow to predict whether a user would pick up a call or not. Using an app publicly available for Android phones, we logged anonymous data from 31311 calls of 418 different users. The data shows that information easily available in mobile phones, such as the time since the last call, the time since the last ringer mode change, or the device posture, can predict call availability with an accuracy of 83.2% (Kappa = .646). Personalized models can increase the accuracy to 87% on average. Features related to when the user was last active turned out to be strong predictors. This shows that simple contextual cues approximating user activity are worthwhile investigating when designing context-aware ubiquitous communication systems.
Publication Year: 2014
Publication Date: 2014-09-13
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 39
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