A systematic assessment of smartphone usage gaps
Authors: Anagnostopoulos, Theodoros 
Hosio, Simo 
Ferreira, Denzil 
Van Berkel, Niels 
Luo, Chu 
Kostakos, Vassilis 
Goncalves, Jorge 
Issue Date: 7-May-2016
Conference: CHI '16: CHI Conference on Human Factors in Computing Systems, 7-12 May 2016, San Jose California, USA 
Book: CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems 
Keywords: Classification models, ESM, Human behaviour, Machine learning, Mobile devices, Phone usage, Session
Abstract: 
Researchers who analyse smartphone usage logs often make the assumption that users who lock and unlock their phone for brief periods of time (e.g., less than a minute) are continuing the same "session" of interaction. However, this assumption is not empirically validated, and in fact different studies apply different arbitrary thresholds in their analysis. To validate this assumption, we conducted a field study where we collected user-labelled activity data through ESM and sensor logging. Our results indicate that for the majority of instances where users return to their smartphone, i.e., unlock their device, they in fact begin a new session as opposed to continuing a previous one. Our findings suggest that the commonly used approach of ignoring brief standby periods is not reliable, but optimisation is possible. We therefore propose various metrics related to usage sessions and evaluate various machine learning approaches to classify gaps in usage.
ISBN: 978-1-4503-3362-7
DOI: 10.1145/2858036.2858348
URI: https://uniwacris.uniwa.gr/handle/3000/2697
Type: Conference Paper
Department: Department of Business Administration 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου

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