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Crowdsourcing Health Labels: Inferring Body Weight from Profile Pictures

Authors :
Weber, Ingmar
Mejova, Yelena
Publication Year :
2016

Abstract

To use social media for health-related analysis, one key step is the detection of health-related labels for users. But unlike transient conditions like flu, social media users are less vocal about chronic conditions such as obesity, as users might not tweet "I'm still overweight". As, however, obesity-related conditions such as diabetes, heart disease, osteoarthritis, and even cancer are on the rise, this obese-or-not label could be one of the most useful for studies in public health. In this paper we investigate the feasibility of using profile pictures to infer if a user is overweight or not. We show that this is indeed possible and further show that the fraction of labeled-as-overweight users is higher in U.S. counties with higher obesity rates. Going from public to individual health analysis, we then find differences both in behavior and social networks, for example finding users labeled as overweight to have fewer followers.<br />Comment: This is a preprint of an article appearing at ACM DigitalHealth 2016

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1602.07185
Document Type :
Working Paper