Is Saki #delicious?
Name
p509-ofli.pdf
Description
Published version
Size
3.23 MB
Format
Adobe PDF
Checksum (MD5)
8c53b24f80540d47b3f1a4e9847dc7e8
Author(s)
Ofli, Ferda
Aytar, Yusuf
Weber, Ingmar
al Hammouri, Raggi
Torralba, Antonio
Alternative Title
Is Saki #delicious?: The Food Perception Gap on Instagram and Its Relation to Health
Date Issued
April 2017
Journal
Proceedings of the 26th International Conference on World Wide Web
Publisher
ACM Press
Citation
Ofli, Ferda et al. "Is Saki #delicious?: The Food Perception Gap on Instagram and Its Relation to Health." Proceedings of the 26th International Conference on World Wide Web, April 2017, Perth, Australia, International World Wide Web Conference Committee, April 2017 © 2017 International World Wide Web Conference Committee (IW3C2)
Version
Final published version
Abstract
Food is an integral part of our life and what and how much we eat crucially affects our health. Our food choices largely depend on how we perceive certain characteristics of food, such as whether it is healthy, delicious or if it qualifies as a salad. But these perceptions differ from person to person and one person’s “single lettuce leaf” might be another person’s “side salad”. Studying how food is perceived in relation to what it actually is typically involves a laboratory setup. Here we propose to use recent advances in image recognition to tackle this problem. Concretely, we use data for 1.9 million images from Instagram from the US to look at systematic differences in how a machine would objectively label an image compared to how a human subjectively does. We show that this difference, which we call the “perception gap”, relates to a number of health outcomes observed at the county level. To the best of our knowledge, this is the first time that image recognition is being used to study the “misalignment” of how people describe food images vs. what they actually depict.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3038912.3052663
