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How age and gender affect smartphone usage

Published: 12 September 2016 Publication History

Abstract

Smartphone usage is a hot topic in pervasive computing due to their popularity and personal aspect. We present our initial results from analyzing how individual differences, such as gender and age, affect smartphone usage. The dataset comes from a large scale longitudinal study, the Menthal project. We select a sample of 30, 677 participants, from which 16, 147 are males and 14, 523 are females, with a median age of 21 years. These have been tracked for at least 28 days and they have submitted their demographic data through a questionnaire. The ongoing experiment has been started in January 2014 and we have used our own mobile data collection and analysis framework. Females use smartphones for longer periods than males, with a daily mean of 166.78 minutes vs. 154.26 minutes. Younger participants use their phones longer and usage is directed towards entertainment and social interactions through specialized apps. Older participants use it less and mainly for getting information or using it as a classic phone.

References

[1]
Ionut Andone, Konrad Błaszkiewicz, Mark Eibes, Boris Trendafilov, Christian Montag, and Alexander Markowetz. 2016a. Menthal - Running a Science Project as a Start-Up. In Computing in Mental Health, Workshop at CHI 2016. ACM.
[2]
Ionut Andone, Konrad Błaszkiewicz, Mark Eibes, Boris Trendafilov, Christian Montag, and Alexander Markowetz. 2016b. Menthal: A Framework for Mobile Data Collection and Analysis. In Ubicomp/ISWC 2016 Adjunct. ACM.
[3]
Ricardo Baeza-Yates, Di Jiang, Fabrizio Silvestri, and Beverly Harrison. 2015. Predicting the next app that you are going to use. In Proc. WSDM 2015. ACM, 285--294.
[4]
Matthias Böhmer, Brent Hecht, Johannes Schöning, Antonio Krüger, and Gernot Bauer. 2011. Falling asleep with Angry Birds, Facebook and Kindle: a large scale study on mobile application usage. In Proc. MobileHCI 2011. ACM, 47--56.
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CIA. 2015. The World Factbook 2014-15. GPO.
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Ericsson. 2016. Ericsson Mobility Report. (2016).
[7]
Denzil Ferreira, Anind K Dey, and Vassilis Kostakos. 2011. Understanding human-smartphone concerns: a study of battery life. In Pervasive computing. Springer, 19--33.
[8]
Andrea Girardello and Florian Michahelles. 2010. AppAware: which mobile applications are hot?. In Proc. MobileHCI 2010. ACM, 431--434.
[9]
Daniel T Wagner, Andrew Rice, and Alastair R Beresford. 2014. Device Analyzer: Large-scale mobile data collection. ACM SIGMETRICS Performance Evaluation Review 41, 4 (2014), 53--56.

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    cover image ACM Conferences
    UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct
    September 2016
    1807 pages
    ISBN:9781450344623
    DOI:10.1145/2968219
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Publication History

    Published: 12 September 2016

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    Author Tags

    1. data mining
    2. mobile computing
    3. mobile devices
    4. smartphone usage
    5. user behavior observation

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    • (2024)Does putting down your smartphone make you happier? the effects of restricting digital media on well-beingPLOS ONE10.1371/journal.pone.030691019:10(e0306910)Online publication date: 14-Oct-2024
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