research-article

Understanding usage states on mobile devices

Authors:

Chakajkla Jesdabodi,

Walid MaalejAuthors Info & Claims

UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Pages 1221 - 1225

https://doi.org/10.1145/2750858.2805837

Published: 07 September 2015 Publication History

Abstract

Nowadays, mobile apps are used for nearly every situation: for planning the day, communicating with colleagues, ordering goods, or entertaining and socializing. To understand users expectations in each situation and to provide context-aware services, researchers and app vendors started to capture users' interaction with the smartphone and to model user's behavior. This paper reports on a behavioral study based on app usage data logged over one year and the corresponding apps descriptions from the app store. Using Topic Modeling and clustering techniques, we segmented the usage data into meaningful clusters that correspond to different "states", in which users normally use their smartphone, e.g. socializing or consuming media. Researchers and app-vendors can use the insights from our work to improve their contextual recommendation techniques and the overall usage experience.

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Cited By

Lee SChoi JLee JWasi MChoi HKo SOh SShin IGanesan DLane NShi W(2024)MobileGPT: Augmenting LLM with Human-like App Memory for Mobile Task AutomationProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3690682(1119-1133)Online publication date: 4-Dec-2024
https://dl.acm.org/doi/10.1145/3636534.3690682
Dambra SBilge LKotzias PShen YCaballero JCalandrino JTroncoso C(2023)One size does not fit allProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620555(5683-5700)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.5555/3620237.3620555
Chen YLee YKao KTsai JLiang EChiu WShih FChang Y(2023)Are You Killing Time? Predicting Smartphone Users’ Time-killing Moments via Fusion of Smartphone Sensor Data and ScreenshotsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580689(1-19)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580689
Show More Cited By

Index Terms

Understanding usage states on mobile devices
1. Information systems
  1. Information retrieval
    1. Users and interactive retrieval
      1. Personalization
  2. World Wide Web
    1. Web searching and information discovery
      1. Personalization

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cover image ACM Conferences

UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 2015

1302 pages

ISBN:9781450335744

DOI:10.1145/2750858

General Chairs:
Kenji Mase
Nagoya University, JP
,
Marc Langheinrich
Università della Svizzera italiana (USI), CH
,
Daniel Gatica-Perez
IDIAP-EPFL, CH
,
Program Chairs:
Hans Gellersen
Lancaster University, UK
,
Tanzeem Choudhury
Cornell University
,
Koji Yatani
Univerisity of Tokyo, JP

Copyright © 2015 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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Yahoo! Japan: Yahoo! Japan
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
FX Palo Alto Laboratory, Inc.: FX Palo Alto Laboratory, Inc.
Google Inc.
ACM: Association for Computing Machinery
Rakuten Institute of Technology: Rakuten Institute of Technology
Microsoft: Microsoft
Bell Labs: Bell Laboratories
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
KDDI
Panasonic: Panasonic Corporation
NTT DoCoMo
Telefónica: Telefónica
ISTC-PC: Intel Science and Technology Center for Pervasive Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 September 2015

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UbiComp '15

Sponsor:

Yahoo! Japan
SIGMOBILE
FX Palo Alto Laboratory, Inc.
ACM
Rakuten Institute of Technology
Microsoft
Bell Labs
SIGCHI
Panasonic
Telefónica
ISTC-PC

UbiComp '15: The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 7 - 11, 2015

Osaka, Japan

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UbiComp '15 Paper Acceptance Rate 101 of 394 submissions, 26%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Lee SChoi JLee JWasi MChoi HKo SOh SShin IGanesan DLane NShi W(2024)MobileGPT: Augmenting LLM with Human-like App Memory for Mobile Task AutomationProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3690682(1119-1133)Online publication date: 4-Dec-2024
https://dl.acm.org/doi/10.1145/3636534.3690682
Dambra SBilge LKotzias PShen YCaballero JCalandrino JTroncoso C(2023)One size does not fit allProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620555(5683-5700)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.5555/3620237.3620555
Chen YLee YKao KTsai JLiang EChiu WShih FChang Y(2023)Are You Killing Time? Predicting Smartphone Users’ Time-killing Moments via Fusion of Smartphone Sensor Data and ScreenshotsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580689(1-19)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580689
Tian YZhou KPelleg D(2023)Characterization and Prediction of Mobile TasksACM Transactions on Information Systems10.1145/352271141:1(1-39)Online publication date: 9-Jan-2023
https://dl.acm.org/doi/10.1145/3522711
Li TFan YLi YTarkoma SHui P(2023)Understanding the Long-Term Evolution of Mobile App UsageIEEE Transactions on Mobile Computing10.1109/TMC.2021.309866422:2(1213-1230)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TMC.2021.3098664
Wan LZhang JLiu M(2023)To Leave or Not to Leave? Understanding Task Stickiness in Smartphone Activity RecommendationsHCI International 2023 Posters10.1007/978-3-031-35989-7_89(695-701)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35989-7_89
Liang SWu DDong J(2022)Understanding the Paths and Patterns of App-Switching Experiences in Mobile SearchesSustainability10.3390/su14201299214:20(12992)Online publication date: 11-Oct-2022
https://doi.org/10.3390/su142012992
Dammak HMejri ORiahi MMoussa F(2022)User Group Profiling through Mobile Application Usage Behavior2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)10.1109/SETIT54465.2022.9875502(278-285)Online publication date: 28-May-2022
https://doi.org/10.1109/SETIT54465.2022.9875502
Li TXia TWang HTu ZTarkoma SHan ZHui P(2022)Smartphone App Usage Analysis: Datasets, Methods, and ApplicationsIEEE Communications Surveys & Tutorials10.1109/COMST.2022.316317624:2(937-966)Online publication date: Oct-2023
https://doi.org/10.1109/COMST.2022.3163176
Friedrichs BTurner LAllen S(2022)Utilising the co-occurrence of user interface interactions as a risk indicator for smartphone addictionPervasive and Mobile Computing10.1016/j.pmcj.2022.10167786:COnline publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1016/j.pmcj.2022.101677
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