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Social sensing for epidemiological behavior change

Authors:

Manuel Cebrian,

Alex PentlandAuthors Info & Claims

UbiComp '10: Proceedings of the 12th ACM international conference on Ubiquitous computing

Pages 291 - 300

https://doi.org/10.1145/1864349.1864394

Published: 26 September 2010 Publication History

Abstract

An important question in behavioral epidemiology and public health is to understand how individual behavior is affected by illness and stress. Although changes in individual behavior are intertwined with contagion, epidemiologists today do not have sensing or modeling tools to quantitatively measure its effects in real-world conditions. In this paper, we propose a novel application of ubiquitous computing. We use mobile phone based co-location and communication sensing to measure characteristic behavior changes in symptomatic individuals, reflected in their total communication, interactions with respect to time of day (e.g., late night, early morning), diversity and entropy of face-to-face interactions and movement. Using these extracted mobile features, it is possible to predict the health status of an individual, without having actual health measurements from the subject. Finally, we estimate the temporal information flux and implied causality between physical symptoms, behavior and mental health.

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Cited By

Barnett NSokolovsky AMeisel MForkus SJackson K(2024)A Bluetooth-Based Smartphone App for Detecting Peer Proximity: Protocol for Evaluating Functionality and ValidityJMIR Research Protocols10.2196/5024113(e50241)Online publication date: 5-Apr-2024
https://doi.org/10.2196/50241
Tlachac MHeinz MReisch MOgden S(2024)Symptom Detection with Text Message Log Distributions for Holistic Depression and Anxiety ScreeningProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435548:1(1-28)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643554
Balliu BDouglas CSeok DShenhav LWu YChatzopoulou DKaiser WChen VKim JDeverasetty SArnaudova IGibbons RCongdon ECraske MFreimer NHalperin ESankararaman SFlint J(2024)Personalized mood prediction from patterns of behavior collected with smartphonesnpj Digital Medicine10.1038/s41746-024-01035-67:1Online publication date: 28-Feb-2024
https://doi.org/10.1038/s41746-024-01035-6
Show More Cited By

Index Terms

Social sensing for epidemiological behavior change
1. Computing methodologies
  1. Machine learning
2. Information systems
  1. Information systems applications

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Published In

cover image ACM Conferences

UbiComp '10: Proceedings of the 12th ACM international conference on Ubiquitous computing

September 2010

366 pages

ISBN:9781605588438

DOI:10.1145/1864349

General Chairs:
Jakob E. Bardram
IT University of Copenhagen, Denmark
,
Marc Langheinrich
University of Lugano, Switzerland
,
Program Chairs:
Khai N. Truong
University of Toronto, Canada
,
Paddy Nixon
University College Dublin, Ireland

Copyright © 2010 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 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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University of Florida: University of Florida

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 September 2010

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Ubicomp '10

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Ubicomp '10: The 2010 ACM Conference on Ubiquitous Computing

September 26 - 29, 2010

Copenhagen, Denmark

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UbiComp '10 Paper Acceptance Rate 39 of 202 submissions, 19%;

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

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Cited By

Barnett NSokolovsky AMeisel MForkus SJackson K(2024)A Bluetooth-Based Smartphone App for Detecting Peer Proximity: Protocol for Evaluating Functionality and ValidityJMIR Research Protocols10.2196/5024113(e50241)Online publication date: 5-Apr-2024
https://doi.org/10.2196/50241
Tlachac MHeinz MReisch MOgden S(2024)Symptom Detection with Text Message Log Distributions for Holistic Depression and Anxiety ScreeningProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435548:1(1-28)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643554
Balliu BDouglas CSeok DShenhav LWu YChatzopoulou DKaiser WChen VKim JDeverasetty SArnaudova IGibbons RCongdon ECraske MFreimer NHalperin ESankararaman SFlint J(2024)Personalized mood prediction from patterns of behavior collected with smartphonesnpj Digital Medicine10.1038/s41746-024-01035-67:1Online publication date: 28-Feb-2024
https://doi.org/10.1038/s41746-024-01035-6
Lee TLee HLee JKim J(2023)Ensemble Approach to Combining Episode Prediction Models Using Sequential Circadian Rhythm Sensor Data from Mental Health PatientsSensors10.3390/s2320854423:20(8544)Online publication date: 18-Oct-2023
https://doi.org/10.3390/s23208544
Periñán-Pascual C(2023)From Smart City to Smart SocietyApplied Ontology10.3233/AO-23028118:3(263-306)Online publication date: 7-Nov-2023
https://dl.acm.org/doi/10.3233/AO-230281
Jackson KMeisel MSokolovsky aChen KBarnett N(2023)Detecting and Understanding Social Influence during Drinking Situations: A Study Protocol for Establishing Feasibility and Acceptability of a Bluetooth-based Sensor (Preprint)JMIR Research Protocols10.2196/50650Online publication date: 7-Jul-2023
https://doi.org/10.2196/50650
Hermsen SVan Abswoude FSteenbergen B(2023)The Effect of Social Networks on Active Living in Adolescents: Qualitative Focus Group StudyJMIR Formative Research10.2196/463507(e46350)Online publication date: 5-Oct-2023
https://doi.org/10.2196/46350
Dang TSpathis DGhosh AMascolo C(2023)Human-centred artificial intelligence for mobile health sensing: challenges and opportunitiesRoyal Society Open Science10.1098/rsos.23080610:11Online publication date: 15-Nov-2023
https://doi.org/10.1098/rsos.230806
Zhou SZhao JZhang L(2022)Application of Artificial Intelligence on Psychological Interventions and Diagnosis: An OverviewFrontiers in Psychiatry10.3389/fpsyt.2022.81166513Online publication date: 17-Mar-2022
https://doi.org/10.3389/fpsyt.2022.811665
Qirtas MZafeiridi EPesch DWhite E(2022)Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping ReviewJMIR mHealth and uHealth10.2196/3463810:4(e34638)Online publication date: 12-Apr-2022
https://doi.org/10.2196/34638
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