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Exploring sustainable European gastronomy and recipes using Natural Language Processing

Reynolds, C. ORCID: 0000-0002-1073-7394 (2021). Exploring sustainable European gastronomy and recipes using Natural Language Processing. Paper presented at the Online Workshop on Computational Approaches in Eating Behavior Research Computational Approaches in Eating Behavior Research, 18th January 2021.

Abstract

Analysis of digitised or digital recipes is a new and upcoming field of research, with publications linked to nutritional and health studies, computational linguistics, computational gastronomy, online shopping recommendations, and the semantic web published over the last 3-5 years. However, contemporary recipe analysis is underdeveloped in terms of links to sustainability due to the complexity of linking environmental impact databases to food terminology, which is time-consuming without Artificial Intelligence (AI) and Natural Language Processing (NLP) tools. It is only in the last few years that these methods have been applied to combining recipes, food texts, and other environmental, nutritional, and economic databases, but this work is still embryonic. In addition, the cooking methods described in recipes have not been investigated – but recent research shows that cooking method can make a considerable environmental impact (up to 60% of some ingredients). In this paper, I discuss the potential to use NLP to analyse nutritional and sustainability aspects of ‘sustainable’, ‘plant based’, ‘vegan’ or ‘vegetarian’ recipes from different European gastronomic traditions or cultures (UK, Dutch, and German), assessing the ingredients used, and the methods of cooking. This is to generate understanding from an interdisciplinary perspective of how gastronomic cultures differ in their approaches to sustainable food; these findings may in turn help all food cultures shift towards more sustainable gastronomy. I present the preliminary visualisations of pilot work carried out in 2020, and describe the basic methodology of the work, the datasets and software required, and perceived challenges that may occur in the project that will be carried out in 2021. I also present possible areas for future collaboration.

Publication Type: Conference or Workshop Item (Lecture)
Publisher Keywords: digital recipes; Natural Language Processing; Artificial Intelligence; nutritional and health studies; computational linguistics; computational gastronomy; online shopping recommendations
Subjects: G Geography. Anthropology. Recreation > GT Manners and customs
H Social Sciences > HM Sociology
P Language and Literature > P Philology. Linguistics
Departments: School of Arts & Social Sciences > Sociology > Food Policy
Date Deposited: 19 Jan 2021 09:47
URI: https://openaccess.city.ac.uk/id/eprint/25529
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