Where am I? Predicting user location semantics from engagement with smartphone notifications

Publication Type:

Journal Article


Journal of Ambient Intelligence and Humanized Computing, Springer (2020)




Interruption management, Location Services, Mobile notifications, Semantic location labelling


Location semantics are important for the delivery of context-aware ubiquitous services to users, such as the contextually-relevant handling of interruptions on mobile devices. For such purposes, user coordinates can be used to query global venue databases, to get back the likely venue (and its categories) where the user is located. This potentially compromises user privacy, allowing service providers to track users. We analyse data from a longitudinal study of 44 participants (university students and staff in Patras, Greece), including notification handling, device state and location information. Using semantic labels from the Google Places API as ground truth, we demonstrate that it is possible to semantically label a user’s location based on their notification handling behaviour, even when location coordinates are obfuscated so as not to precisely match known venue locations. On the other hand, the reliability of this ground truth is questioned through a crowdsourcing exercise. We demonstrate that Places API data can only be reliably used for some venue categories, and recommend best practices for using such data to establish ground truth in location context aware services.

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