Social sensing for epidemiological behavior change
Name
Pentland_Social Sensing.pdf
Size
1.1 MB
Format
Adobe PDF
Checksum (MD5)
a3318dab9dc21a0e777c106b6d7158d8
Author(s)
Madan, Anmol Prem Prakash
Cebrian, Manuel
Lazer, David
Pentland, Alex Paul
Date Issued
September 2010
Journal
Proceedings of the 12th ACM International Conference on Ubiquitous Computing, Ubicomp '10
Publisher
Association for Computing Machinery
Citation
Madan, Anmol et al. “Social sensing for epidemiological behavior change.” ACM Press, 2010. 291.
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/1864349.1864394
