A Systematic Assessment of Smartphone Usage Gaps (bibtex)
by van Berkel, Niels, Luo, Chu, Anagnostopoulos, Theodoros, Ferreira, Denzil, Goncalves, Jorge, Hosio, Simo and Kostakos, Vassilis
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.
Reference:
N. van Berkel, C. Luo, T. Anagnostopoulos, D. Ferreira, J. Goncalves, S. Hosio, V. Kostakos, "A Systematic Assessment of Smartphone Usage Gaps", in Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems (CHI'16), 2016, 4711-4721.
Bibtex Entry:
@inproceedings{Berkel2016SmartphoneGaps,
	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.},
	Author = {van Berkel, Niels and Luo, Chu and Anagnostopoulos, Theodoros and Ferreira, Denzil and Goncalves, Jorge and Hosio, Simo and Kostakos, Vassilis},
	Booktitle = {Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems},
	Doi = {10.1145/2858036.2858348},
	Location = {CHI'16},
	Pages = {4711-4721},
	Title = {A Systematic Assessment of Smartphone Usage Gaps},
	Type = {Conference Paper},
	Url = {https://nielsvanberkel.com/files/publications/chi2016a.pdf},
	Year = {2016}}
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