Understanding Cross-Cultural Visual Food Tastes with Online Recipe Platforms

  • Qing Zhang University of Regensburg
  • Christoph Trattner University of Bergen
  • Bernd Ludwig University of Regensburg
  • David Elsweiler University of Regensburg

Abstract

Traces of human behaviour with online recipe portals offer an opportunity to employ a data-driven approach to the study of food culture. Here, we focus on understanding visual aspects of food preference by analysing datasets from China, Germany, and US. Predictive modelling with low-level image features and Deep Neural Network image embeddings show differences in recipe images across datasets and between recipes with high and low appreciation within datasets. Our findings demonstrate the utility of the approach for studying visual aspects food culture.

Published
2019-07-06
How to Cite
Zhang, Q., Trattner, C., Ludwig, B., & Elsweiler, D. (2019). Understanding Cross-Cultural Visual Food Tastes with Online Recipe Platforms. Proceedings of the International AAAI Conference on Web and Social Media, 13(01), 671-674. Retrieved from https://aaai.org/ojs/index.php/ICWSM/article/view/3270