@inproceedings{e2c9daa64ee34d318d62576d00cf51ab,
title = "Using computer vision to study the effects of BMI on online popularity and weight-based homophily",
abstract = "Increasing prevalence of obesity has disconcerting implications for communities, for nations and, most importantly, for individuals in aspects ranging from quality of life, longevity and health, to social and financial prosperity. Therefore, researchers from a variety of backgrounds study obesity from all angles. In this paper, we use a state-of-the-art computer vision system to predict a person{\textquoteright}s body-mass index (BMI) from their social media profile picture and demonstrate the type of analyses this approach enables using data from two culturally diverse settings – the US and Qatar. Using large amounts of Instagram profile pictures, we show that (i) thinner profile pictures have more followers, and that (ii) there is weight-based network homophily in that users with a similar BMI tend to cluster together. To conclude, we also discuss the challenges and limitations related to inferring various user attributes from photos.",
keywords = "Body-mass index, Computer vision, Social media",
author = "Enes Kocabey and Ferda Ofli and Javier Marin and Antonio Torralba and Ingmar Weber",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 10th Conference on Social Informatics, SocInfo 2018 ; Conference date: 25-09-2018 Through 28-09-2018",
year = "2018",
doi = "10.1007/978-3-030-01159-8_12",
language = "English",
isbn = "9783030011581",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "129--138",
editor = "Steffen Staab and Olessia Koltsova and Ignatov, {Dmitry I.}",
booktitle = "Social Informatics - 10th International Conference, SocInfo 2018, Proceedings",
address = "Germany",
}