research-article

A Large-Scale, Long-Term Analysis of Mobile Device Usage Characteristics

Authors:

Philipp Hintze,

Rainhard D. Findling,

René MayrhoferAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 1, Issue 2

Article No.: 13, Pages 1 - 21

https://doi.org/10.1145/3090078

Published: 30 June 2017 Publication History

Abstract

Today, mobile devices like smartphones and tablets have become an indispensable part of people's lives, posing many new questions e.g., in terms of interaction methods, but also security. In this paper, we conduct a large scale, long term analysis of mobile device usage characteristics like session length, interaction frequency, and daily usage in locked and unlocked state with respect to location context and diurnal pattern. Based on detailed logs from 29,279 mobile phones and tablets representing a total of 5,811 years of usage time, we identify and analyze 52.2 million usage sessions with some participants providing data for more than four years.

Our results show that context has a highly significant effect on both frequency and extent of mobile device usage, with mobile phones being used twice as much at home compared to in the office. Interestingly, devices are unlocked for only 46 % of the interactions. We found that with an average of 60 interactions per day, smartphones are used almost thrice as often as tablet devices (23), while usage sessions on tablets are three times longer, hence are used almost for an equal amount of time throughout the day. We conclude that usage session characteristics differ considerably between tablets and smartphones. These results inform future approaches to mobile interaction as well as security.

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Cited By

Hwang JKim SPark DSong YHan JChoi SCho SWon YBagchi SZhang Y(2024)ZMSProceedings of the 2024 USENIX Conference on Usenix Annual Technical Conference10.5555/3691992.3692003(173-189)Online publication date: 10-Jul-2024
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Chen ZFilkov VRay BZhou M(2024)A Comprehensive Study of Privacy Leakage Vulnerability in Android App LogsProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695609(2510-2513)Online publication date: 27-Oct-2024
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Zhang YLi TYuan YXu FYang FSun FLi Y(2024)Demand-driven Urban Facility Visit PredictionACM Transactions on Intelligent Systems and Technology10.1145/362523315:2(1-24)Online publication date: 22-Feb-2024
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Index Terms

A Large-Scale, Long-Term Analysis of Mobile Device Usage Characteristics
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
  2. Ubiquitous and mobile computing
    1. Empirical studies in ubiquitous and mobile computing
    2. Ubiquitous and mobile devices
      1. Mobile devices
      2. Tablet computers

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 1, Issue 2

June 2017

665 pages

EISSN:2474-9567

DOI:10.1145/3120957

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Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 30 June 2017

Accepted: 01 May 2017

Revised: 01 April 2017

Received: 01 February 2017

Published in IMWUT Volume 1, Issue 2

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Cited By

Hwang JKim SPark DSong YHan JChoi SCho SWon YBagchi SZhang Y(2024)ZMSProceedings of the 2024 USENIX Conference on Usenix Annual Technical Conference10.5555/3691992.3692003(173-189)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.5555/3691992.3692003
Chen ZFilkov VRay BZhou M(2024)A Comprehensive Study of Privacy Leakage Vulnerability in Android App LogsProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695609(2510-2513)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695609
Zhang YLi TYuan YXu FYang FSun FLi Y(2024)Demand-driven Urban Facility Visit PredictionACM Transactions on Intelligent Systems and Technology10.1145/362523315:2(1-24)Online publication date: 22-Feb-2024
https://dl.acm.org/doi/10.1145/3625233
Lu TZheng HZhang TXu XGuo A(2024)InteractOut: Leveraging Interaction Proxies as Input Manipulation Strategies for Reducing Smartphone OveruseProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642317(1-19)Online publication date: 11-May-2024
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Roffarello ADe Russis L(2023)Achieving Digital Wellbeing Through Digital Self-control Tools: A Systematic Review and Meta-analysisACM Transactions on Computer-Human Interaction10.1145/357181030:4(1-66)Online publication date: 12-Sep-2023
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Liang YLiu LHuangfu LWang ZGuo B(2023)DeepApp: characterizing dynamic user interests for mobile application recommendationWorld Wide Web10.1007/s11280-023-01161-326:5(2623-2645)Online publication date: 2-May-2023
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Yerebakan MHu BBarbir ALin MDennerlein J(2022)Evaluating the impact of writing surface and configuration on muscle activation level during a handwriting task: An exploratory studyWork10.3233/WOR-20524271:4(1183-1191)Online publication date: 21-Apr-2022
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Schneegass CSigethy SMitrevska TEiband MBuschek D(2022)UnlockLearning – Investigating the Integration of Vocabulary Learning Tasks into the Smartphone Authentication Processi-com10.1515/icom-2021-003721:1(157-174)Online publication date: 1-Apr-2022
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