Is Saki #delicious? The food perception gap on instagram and its relation to health

Ferda Ofli, Yusuf Aytar, Ingmar Weber, Raggi Al Hammouri, Antonio Torralba

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

56 Citations (Scopus)

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.

Original languageEnglish
Title of host publication26th International World Wide Web Conference, WWW 2017
PublisherInternational World Wide Web Conferences Steering Committee
Pages509-518
Number of pages10
ISBN (Print)9781450349130
DOIs
Publication statusPublished - 2017
Event26th International World Wide Web Conference, WWW 2017 - Perth, Australia
Duration: 3 Apr 20177 Apr 2017

Publication series

Name26th International World Wide Web Conference, WWW 2017

Conference

Conference26th International World Wide Web Conference, WWW 2017
Country/TerritoryAustralia
CityPerth
Period3/04/177/04/17

Keywords

  • Computer vision
  • Food
  • Instagram
  • Public health

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