research-article

The social fMRI: measuring, understanding, and designing social mechanisms in the real world

Authors:

Alex PentlandAuthors Info & Claims

UbiComp '11: Proceedings of the 13th international conference on Ubiquitous computing

Pages 445 - 454

https://doi.org/10.1145/2030112.2030171

Published: 17 September 2011 Publication History

Abstract

A key challenge of data-driven social science is the gathering of high quality multi-dimensional datasets. A second challenge relates to design and execution of structured experimental interventions in-situ, in a way comparable to the reliability and intentionality of ex-situ laboratory experiments. In this paper we introduce the Friends and Family study, in which a young-family residential community is transformed into a living laboratory. We employ a ubiquitous computing approach that combines extremely rich data collection in terms of signals, dimensionality, and throughput, together with the ability to conduct targeted experimental interventions with study populations. We present our mobile-phone-based social and behavioral sensing system, which has been deployed for over a year now. Finally, we describe a novel tailored intervention aimed at increasing physical activity in the subject population. Results demonstrate the value of social factors for motivation and adherence, and allow us to quantify the contribution of different incentive mechanisms.

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Cited By

Zhang HIbrahim AParsia BPoliakoff EHarper S(2022)Passive social sensing with smartphones: a systematic reviewComputing10.1007/s00607-022-01112-2105:1(29-51)Online publication date: 12-Aug-2022
https://doi.org/10.1007/s00607-022-01112-2
Nishiyama YFerreira DSasaki WOkoshi TNakazawa JDey ASezaki KTentori MWeibel NVan Laerhoven KAbowd GSalim F(2020)Using iOS for inconspicuous data collectionAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers10.1145/3410530.3414369(261-266)Online publication date: 10-Sep-2020
https://dl.acm.org/doi/10.1145/3410530.3414369
Alavi HLalanne DRogers Y(2020)The Five Strands of Living LabACM Transactions on Computer-Human Interaction10.1145/338095827:2(1-26)Online publication date: 11-Mar-2020
https://dl.acm.org/doi/10.1145/3380958
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Index Terms

The social fMRI: measuring, understanding, and designing social mechanisms in the real world
1. Information systems
  1. Information systems applications

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Published In

cover image ACM Conferences

UbiComp '11: Proceedings of the 13th international conference on Ubiquitous computing

September 2011

668 pages

ISBN:9781450306300

DOI:10.1145/2030112

General Chairs:
James Landay
University of Washington, USA & Microsoft Research Asia, China
,
Yuanchun Shi
Tsinghua University, China
,
Program Chairs:
Donald J. Patterson
University of California, Irvine, USA
,
Yvonne Rogers
Open University, UK
,
Xing Xie
Microsoft Research Asia, China

Copyright © 2011 ACM.

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New York, NY, United States

Publication History

Published: 17 September 2011

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Ubicomp '11

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Ubicomp '11: The 2011 ACM Conference on Ubiquitous Computing

September 17 - 21, 2011

Beijing, China

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

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Cited By

Zhang HIbrahim AParsia BPoliakoff EHarper S(2022)Passive social sensing with smartphones: a systematic reviewComputing10.1007/s00607-022-01112-2105:1(29-51)Online publication date: 12-Aug-2022
https://doi.org/10.1007/s00607-022-01112-2
Nishiyama YFerreira DSasaki WOkoshi TNakazawa JDey ASezaki KTentori MWeibel NVan Laerhoven KAbowd GSalim F(2020)Using iOS for inconspicuous data collectionAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers10.1145/3410530.3414369(261-266)Online publication date: 10-Sep-2020
https://dl.acm.org/doi/10.1145/3410530.3414369
Alavi HLalanne DRogers Y(2020)The Five Strands of Living LabACM Transactions on Computer-Human Interaction10.1145/338095827:2(1-26)Online publication date: 11-Mar-2020
https://dl.acm.org/doi/10.1145/3380958
Doherty KBalaskas ADoherty G(2020)The Design of Ecological Momentary Assessment TechnologiesInteracting with Computers10.1093/iwcomp/iwaa01932:3(257-278)Online publication date: 27-Aug-2020
https://doi.org/10.1093/iwcomp/iwaa019
Nishiyama YFerreira DEigen YSasaki WOkoshi TNakazawa JDey ASezaki K(2020)IOS Crowd–Sensing Won’t Hurt a Bit!: AWARE Framework and Sustainable Study Guideline for iOS PlatformDistributed, Ambient and Pervasive Interactions10.1007/978-3-030-50344-4_17(223-243)Online publication date: 10-Jul-2020
https://doi.org/10.1007/978-3-030-50344-4_17
Ornelas EMena RSantana-Mancilla PValderrama E(2019)A mixed methodology to discover what young people know about digital footprintProceedings of the IX Latin American Conference on Human Computer Interaction10.1145/3358961.3358987(1-6)Online publication date: 30-Sep-2019
https://dl.acm.org/doi/10.1145/3358961.3358987
Merrill NChuang JBrewster SFitzpatrick GCox AKostakos V(2019)Models of MindsExtended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290607.3310427(1-10)Online publication date: 2-May-2019
https://dl.acm.org/doi/10.1145/3290607.3310427
Hsu CHristov RLee GZhao MKatabi DBrewster SFitzpatrick GCox AKostakos V(2019)Enabling Identification and Behavioral Sensing in Homes using Radio ReflectionsProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300778(1-13)Online publication date: 2-May-2019
https://dl.acm.org/doi/10.1145/3290605.3300778
Sapiezynski PStopczynski ALassen DLehmann S(2019)Interaction data from the Copenhagen Networks StudyScientific Data10.1038/s41597-019-0325-x6:1Online publication date: 11-Dec-2019
https://doi.org/10.1038/s41597-019-0325-x
Banerjee SChattopadhyay TPal AGarain U(2018)Automation of feature engineering for IoT analyticsACM SIGBED Review10.1145/3231535.323153815:2(24-30)Online publication date: 5-Jun-2018
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