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Plate and Prejudice: Gender Differences in Online Cooking

Published: 13 July 2016 Publication History

Abstract

Historically, there have always been differences in how men and women cook or eat. The reasons for this gender divide have mostly gone in Western culture, but still there is qualitative and anecdotal evidence that men prefer heftier food, that women take care of everyday cooking, and that men cook to impress. In this paper, we show that these differences can also quantitatively be observed in a large dataset of almost 200 thousand members of an online recipe community. Further, we show that, using a set of 88 features, the gender of the cooks can be predicted with fairly good accuracy of 75%, with preference for particular dishes, the use of spices and the use of kitchen utensils being the strongest predictors. Finally, we show the positive impact of our results on online food recipe recommender systems that take gender information into account.

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  • (2024)The Effect of Simulated Contextual Factors on Recipe Rating and Nutritional Intake BehaviourProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638328(97-107)Online publication date: 10-Mar-2024
  • (2023)Understanding and predicting cross-cultural food preferences with online recipe imagesInformation Processing & Management10.1016/j.ipm.2023.10344360:5(103443)Online publication date: Sep-2023
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cover image ACM Conferences
UMAP '16: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
July 2016
366 pages
ISBN:9781450343688
DOI:10.1145/2930238
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 July 2016

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Author Tags

  1. classification
  2. cooking
  3. food recommender systems
  4. gender differences
  5. online food

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  • Research-article

Funding Sources

  • BMBF - German Ministry of Education and Research
  • Austrian Research Promotion Agency (FFG)

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UMAP '16
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UMAP '16: User Modeling, Adaptation and Personalization Conference
July 13 - 17, 2016
Nova Scotia, Halifax, Canada

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UMAP '16 Paper Acceptance Rate 21 of 123 submissions, 17%;
Overall Acceptance Rate 162 of 633 submissions, 26%

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UMAP '25

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Cited By

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  • (2024)The Effect of Simulated Contextual Factors on Recipe Rating and Nutritional Intake BehaviourProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638328(97-107)Online publication date: 10-Mar-2024
  • (2023)Understanding and predicting cross-cultural food preferences with online recipe imagesInformation Processing & Management10.1016/j.ipm.2023.10344360:5(103443)Online publication date: Sep-2023
  • (2021)Photograph Based Evaluation of Consumer Expectation on Healthiness, Fullness, and Acceptance of Sandwiches as Convenience FoodFoods10.3390/foods1005110210:5(1102)Online publication date: 16-May-2021
  • (2021)Increasing Diversity through Dynamic Critique in Conversational Recipe RecommendationsProceedings of the 13th International Workshop on Multimedia for Cooking and Eating Activities10.1145/3463947.3469237(9-16)Online publication date: 21-Aug-2021
  • (2021)Effects and challenges of using a nutrition assistance system: results of a long-term mixed-method studyUser Modeling and User-Adapted Interaction10.1007/s11257-021-09301-y32:5(923-975)Online publication date: 15-Oct-2021
  • (2021)Addressing the complexity of personalized, context-aware and health-aware food recommendations: an ensemble topic modelling based approachJournal of Intelligent Information Systems10.1007/s10844-021-00639-8Online publication date: 12-May-2021
  • (2020)Towards a Knowledge-aware Food Recommender System Exploiting Holistic User ModelsProceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3340631.3394880(333-337)Online publication date: 7-Jul-2020
  • (2020)Hierarchical Attention Network for Visually-Aware Food RecommendationIEEE Transactions on Multimedia10.1109/TMM.2019.294518022:6(1647-1659)Online publication date: Jun-2020
  • (2020)The role of identity and gender in seafood cooking skillsBritish Food Journal10.1108/BFJ-11-2019-0835123:3(1155-1169)Online publication date: 16-Nov-2020
  • (2020)„(No) One-fits-all“ – Eine ernährungssoziologische Analyse zur Beeinflussung des Lebensmittelmarkts durch MillennialsWaren – Wissen – Raum10.1007/978-3-658-30719-6_14(421-447)Online publication date: 17-Nov-2020
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