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You Tweet What You Eat: Studying Food Consumption Through Twitter

Published: 18 April 2015 Publication History

Abstract

Food is an integral part of our lives, cultures, and well-being, and is of major interest to public health. The collection of daily nutritional data involves keeping detailed diaries or periodic surveys and is limited in scope and reach. Alternatively, social media is infamous for allowing its users to update the world on the minutiae of their daily lives, including their eating habits. In this work we examine the potential of Twitter to provide insight into US-wide dietary choices by linking the tweeted dining experiences of 210K users to their interests, demographics, and social networks. We validate our approach by relating the caloric values of the foods mentioned in the tweets to the state-wide obesity rates, achieving a Pearson correlation of 0.77 across the 50 US states and the District of Columbia. We then build a model to predict county-wide obesity and diabetes statistics based on a combination of demographic variables and food names mentioned on Twitter. Our results show significant improvement over previous CHI research (Culotta 2014). We further link this data to societal and economic factors, such as education and income, illustrating that areas with higher education levels tweet about food that is significantly less caloric. Finally, we address the somewhat controversial issue of the social nature of obesity (Christakis & Fowler 2007) by inducing two social networks using mentions and reciprocal following relationships.

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cover image ACM Conferences
CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
April 2015
4290 pages
ISBN:9781450331456
DOI:10.1145/2702123
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: 18 April 2015

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Author Tags

  1. dietary health
  2. food
  3. obesity
  4. social networks
  5. twitter

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CHI '15
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CHI '15: CHI Conference on Human Factors in Computing Systems
April 18 - 23, 2015
Seoul, Republic of Korea

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CHI '15 Paper Acceptance Rate 486 of 2,120 submissions, 23%;
Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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  • (2024)A Survey of the Applications of Text Mining for the Food DomainAlgorithms10.3390/a1705017617:5(176)Online publication date: 25-Apr-2024
  • (2024)Measuring and shaping the nutritional environment via food sales logs: case studies of campus-wide food choice and a call to actionFrontiers in Nutrition10.3389/fnut.2024.123107011Online publication date: 4-Jun-2024
  • (2024)Wellness Influencer Responses to COVID-19 Vaccines on Social Media: A Longitudinal Observational StudyJournal of Medical Internet Research10.2196/5665126(e56651)Online publication date: 27-Nov-2024
  • (2024)Exploring Deep Learning–Based Models for Sociocultural African Food Recognition SystemHuman Behavior and Emerging Technologies10.1155/2024/44433162024:1Online publication date: 18-Sep-2024
  • (2024)MS-GDA: Improving Heterogeneous Recipe Representation via Multinomial Sampling Graph Data AugmentationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/364862020:7(1-23)Online publication date: 20-Feb-2024
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  • (2024)From Text to Taste: Advancing Smart Appliances with Multilingual Recipe Interpretation2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW61823.2024.00007(13-20)Online publication date: 13-May-2024
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  • (2024)Are meat alternatives a moral concern? A comparison of English and Japanese tweetsHumanities and Social Sciences Communications10.1057/s41599-024-03766-z11:1Online publication date: 27-Sep-2024
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