you are what you eat! tracking health through recipe interactions
DESCRIPTION
On today's World Wide Web, social recommender systems have become a commodity regardless of application domain. Even tangible items such as food and clothes have become social. Together with a seemingly endless amount of personalization and recommender systems ranging from movies, music, or consumer products, recipe recommender systems are attracting many users looking for inspiration on the next thing to purchase or cook. There is however a conceptual difference between recommending consumer goods for leisure and entertainment, and recommending food. What people eat has a direct effect on their health, an aspect commonly overlooked in the context of recommendation. In this work, we present an early analysis of users' interactions with recipes (ratings) on the online social network Allrecipes.com. We compare the interaction patterns of users from locations known to have poor health to users from locations known to have good health in order to identify whether there is an observable difference between the two populations. Our results point to a statistically significant difference between the healthy and unhealthy groups, a difference that could potentially be used to create health-conscious, personalized, recommendation services to aid people in their daily lives.TRANSCRIPT
You are What You Eat! Tracking Health Through Recipe Interac8ons
Alan Said TU Del? @alansaid
Alejandro Bellogín Universidad Autónoma de Madrid
@abellogin
RSWeb 2014
Outline • Recommenda8on contexts • Food-‐oriented recommender systems • Linking recipe interac8ons to health
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The different contexts of recommender systems -‐ Consump8on costs -‐ Product longevity -‐ Device
-‐ Health aspects <-‐ Food -‐ “offline” products
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Effects of a recommenda4on Online -‐ Discontent user -‐ Churn -‐ Business effects
Offline -‐ Direct effect on health -‐ Poten8al long-‐term effects
Recommenda8on of tangible items should take into considera8on the effect the item has on the consumer
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Real-‐world recommenda4on effects on users Social – Allrecipes.com Health – County Health Rankings Research Ques4on: Can we iden8fy unhealthy users based on their interac8on pa_erns?
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Allrecipes Data: -‐ 170k user profiles -‐ 54k recipes -‐ 8k ingredients -‐ 17m user-‐recipe interac8ons
Map users onto coun8es Map ingredient usage onto coun8es Map health data onto ingredient usage
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County Health Rankings Health rankings for 3400 US coun8es -‐ Obesity -‐ Heart disease -‐ Premature death -‐ Adult smoking -‐ Etc.
Iden8fy top 5 most/least obese coun8es using County Health Rankings www.countyhealthrankings.org
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The popular ingredient problem
Most used ingredients 51,04% Salt 33,72% Bu_er 30,67% Sugar 27,25% Eggs 26,14% Flour 23,93% Onions 22,79% Garlic 21,96% Water 20,65% Pepper 14,96% Milk 14,85% Vanilla 14,07% Olive oil 12,54% Brown sugar 10,20% Chicken 9,81% Cinnamon 7,96% Parmesan 7,89% Baking soda 7,74% Garlic powder 7,29% Vegetable oil 6,81% Cheddar cheese
55,30% Salt 32,92% Bu_er 31,01% Sugar 27,31% Garlic 26,77% Eggs 25,68% Flour 24,86% Onions 21,54% Water 21,42% Pepper 18,04% Olive oil 14,52% Vanilla 13,23% Milk 12,56% Brown sugar 10,00% Cinnamon 8,75% Baking soda 8,70% Chicken 8,25% Parmesan 7,61% Lemons 7,41% Vegetable oil 6,75% Garlic powder
Low obesity High obesity
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What now?
T-‐test on 110 most used ingredients (% of recipes) in obese and “slim” coun8es shows
p<0.05
Can we use this informa8on to infer the health of a user based on their recipe usage? Yes (we think so)
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Future work • Can we es8mate other health aspects? (diabetes,
smoking, heart disease, premature death, etc.) • Fine-‐grained analysis of recipes and ingredients
– Average opinion of recipes with certain ingredients, e.g. alcohol, candy, etc.
– Geographical recipe and ingredient trends • Recommending healthier alterna8ves to people at risk • Find a healthy “friend” to follow for inspira8on • Linking of cooking interests to health
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Resources • h_p://github.com/alansaid/RecipeCrawler • h_p://github.com/alansaid/RecipeParser
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THANKS! Ques8ons?
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• h_ps://www.flickr.com/photos/hotreactor/36171416/ • h_ps://www.flickr.com/photos/foodswings/4590408656 • h_ps://www.flickr.com/photos/atmtx/4294693128 • h_ps://www.flickr.com/photos/tarale/6689005901 • h_ps://www.flickr.com/photos/stria8c/131012552
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