research-article

Lessons learned from the netsense smartphone study

Authors:

Aaron Striegel,

Shu Liu,

Lei Meng,

Christian Poellabauer,

David Hachen,

Omar LizardoAuthors Info & Claims

ACM SIGCOMM Computer Communication Review, Volume 43, Issue 4

Pages 51 - 56

https://doi.org/10.1145/2534169.2491171

Published: 16 August 2013 Publication History

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Abstract

Over the past few years, smartphones have emerged as one of the most popular mechanisms for accessing content across the Internet driving considerable research to improve wireless performance. A key foundation for such research efforts is the proper understanding of user behavior. However, the gathering of live smartphone data at scale is often difficult and expensive. The focus of this paper is to explore the lessons learned from a two year study of two hundred smart phone users at the University of Notre Dame. In this paper, we offer commentary with regards to the entire process of the study covering aspects including funding considerations, technical architecture design, lessons learned, and recommendations for future efforts gathering live user data.

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Simpson LMillar KCheng AChew HLim C(2023)A Testbed for Automating and Analysing Mobile Devices and Their Applications2023 International Conference on Machine Learning and Cybernetics (ICMLC)10.1109/ICMLC58545.2023.10327947(201-208)Online publication date: 9-Jul-2023
https://doi.org/10.1109/ICMLC58545.2023.10327947
Nurek MMichalski RLizardo ORizoiu M(2023)Predicting Relationship Labels and Individual Personality Traits From Telecommunication History in Social Networks Using Hawkes ProcessesIEEE Access10.1109/ACCESS.2023.323897011(8492-8503)Online publication date: 2023
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Linczuk JGórski PSzymanski BHołyst J(2023)Multidimensional attributes expose Heider balance dynamics to measurementsScientific Reports10.1038/s41598-023-42390-w13:1Online publication date: 20-Sep-2023
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Index Terms

Lessons learned from the netsense smartphone study
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

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Information

Published In

cover image ACM SIGCOMM Computer Communication Review

ACM SIGCOMM Computer Communication Review Volume 43, Issue 4

October 2013

595 pages

ISSN:0146-4833

DOI:10.1145/2534169

Issue’s Table of Contents

HotPlanet '13: Proceedings of the 5th ACM workshop on HotPlanet
August 2013
78 pages
ISBN:9781450321778
DOI:10.1145/2491159
General Chair:
Pan Hui
HKUST/T-labs
,
Program Chairs:
Emiliano Miluzzo
AT&T Labs - Research, USA
,
Hamed Haddadi
Queen Mary University of London, UK

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 ACM 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

New York, NY, United States

Publication History

Published: 16 August 2013

Published in SIGCOMM-CCR Volume 43, Issue 4

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Simpson LMillar KCheng AChew HLim C(2023)A Testbed for Automating and Analysing Mobile Devices and Their Applications2023 International Conference on Machine Learning and Cybernetics (ICMLC)10.1109/ICMLC58545.2023.10327947(201-208)Online publication date: 9-Jul-2023
https://doi.org/10.1109/ICMLC58545.2023.10327947
Nurek MMichalski RLizardo ORizoiu M(2023)Predicting Relationship Labels and Individual Personality Traits From Telecommunication History in Social Networks Using Hawkes ProcessesIEEE Access10.1109/ACCESS.2023.323897011(8492-8503)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3238970
Linczuk JGórski PSzymanski BHołyst J(2023)Multidimensional attributes expose Heider balance dynamics to measurementsScientific Reports10.1038/s41598-023-42390-w13:1Online publication date: 20-Sep-2023
https://doi.org/10.1038/s41598-023-42390-w
Michalski RSerwata DNurek MSzymanski BKazienko PJia T(2022)Temporal network epistemology: On reaching consensus in a real-world settingChaos: An Interdisciplinary Journal of Nonlinear Science10.1063/5.007499232:6Online publication date: 27-Jun-2022
https://doi.org/10.1063/5.0074992
Hachen DWang CSepulvado BLizardo O(2022)Generators or diffusers? Examining differences in the dynamic coupling of context and social ties across multiple types of fociSocial Networks10.1016/j.socnet.2022.02.004Online publication date: Feb-2022
https://doi.org/10.1016/j.socnet.2022.02.004
Flamino JDeVito RLizardo OSzymanski B(2022)Modeling Memory Imprints Induced by Interactions in Social NetworksSocial, Cultural, and Behavioral Modeling10.1007/978-3-031-17114-7_18(186-195)Online publication date: 20-Sep-2022
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Michalski RSzymanski BKazienko PLebiere CLizardo OKulisiewicz M(2021)Social Networks through the Prism of CognitionComplexity10.1155/2021/49639032021Online publication date: 8-Jan-2021
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Talkad Sukumar PBreideband TMartinez GCaruso MRose SSteputis CD'Mello SMark GStriegel A(2021)Designing an Interactive Visualization System for Monitoring Participant Compliance in a Large-Scale, Longitudinal StudyExtended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411763.3443436(1-8)Online publication date: 8-May-2021
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Flamino JSzymanski BBahulkar AChan KLizardo O(2021)Creation, evolution, and dissolution of social groupsScientific Reports10.1038/s41598-021-96805-711:1Online publication date: 1-Sep-2021
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Wang CLizardo OHachen D(2020)Neither influence nor selection: Examining co-evolution of political orientation and social networks in the NetSense and NetHealth studiesPLOS ONE10.1371/journal.pone.023345815:5(e0233458)Online publication date: 29-May-2020
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