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dc.contributor.authorOfli, Ferda
dc.contributor.authorAytar, Yusuf
dc.contributor.authorWeber, Ingmar
dc.contributor.authoral Hammouri, Raggi
dc.contributor.authorTorralba, Antonio
dc.date.accessioned2019-09-10T18:44:13Z
dc.date.available2019-09-10T18:44:13Z
dc.date.issued2017-04
dc.identifier.isbn9781450349130
dc.identifier.urihttps://hdl.handle.net/1721.1/122046
dc.description.abstractFood 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.en_US
dc.language.isoen
dc.publisherACM Pressen_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/3038912.3052663en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceACMen_US
dc.titleIs Saki #delicious?en_US
dc.title.alternativeIs Saki #delicious?: The Food Perception Gap on Instagram and Its Relation to Healthen_US
dc.typeArticleen_US
dc.identifier.citationOfli, 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)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalProceedings of the 26th International Conference on World Wide Weben_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-07-11T16:33:13Z
dspace.date.submission2019-07-11T16:33:14Z


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