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        <title>What does the language of foods say about us?</title>
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    <abstract>In this work we investigate the signal contained in the language of food on social media. We experiment with a dataset of 24 million food-related tweets, and make several observations. First,thelanguageoffoodhaspredictive power. We are able to predict if states in the United States (US) are above the medianratesfortype2diabetesmellitus(T2DM), income, poverty, and education – outperforming previous work by 4–18%. Second, we investigate the effect of socioeconomic factors (income, poverty, and education) on predicting state-level T2DM rates. Socioeconomic factors do improve T2DM prediction, with the greatestimprovementcomingfrompovertyinformation(6%),but,importantly,thelanguage of food adds distinct information that is not captured by socioeconomics. Third, we analyze how the language of food has changed over a five-year period (2013 – 2017), which is indicative of the shift in eating habits in the US during that period. We find several food trends, and that the language of food is used differently by different groups such as differentgenders. Last,weprovideanonlinevisualization tool for real-time queries and semantic analysis.</abstract>
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    <identifier type="doi">10.18653/v1/D19-6212</identifier>
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%0 Conference Proceedings
%T What does the language of foods say about us?
%A Van, Hoang
%A Musa, Ahmad
%A Chen, Hang
%A Kobourov, Stephen
%A Surdeanu, Mihai
%S Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019)
%D 2019
%8 nov
%I Association for Computational Linguistics
%C Hong Kong
%F van-etal-2019-language
%X In this work we investigate the signal contained in the language of food on social media. We experiment with a dataset of 24 million food-related tweets, and make several observations. First,thelanguageoffoodhaspredictive power. We are able to predict if states in the United States (US) are above the medianratesfortype2diabetesmellitus(T2DM), income, poverty, and education – outperforming previous work by 4–18%. Second, we investigate the effect of socioeconomic factors (income, poverty, and education) on predicting state-level T2DM rates. Socioeconomic factors do improve T2DM prediction, with the greatestimprovementcomingfrompovertyinformation(6%),but,importantly,thelanguage of food adds distinct information that is not captured by socioeconomics. Third, we analyze how the language of food has changed over a five-year period (2013 – 2017), which is indicative of the shift in eating habits in the US during that period. We find several food trends, and that the language of food is used differently by different groups such as differentgenders. Last,weprovideanonlinevisualization tool for real-time queries and semantic analysis.
%R 10.18653/v1/D19-6212
%U https://aclanthology.org/D19-6212
%U https://doi.org/10.18653/v1/D19-6212
%P 87-96

Markdown (Informal)

[What does the language of foods say about us?](https://aclanthology.org/D19-6212) (Van et al., EMNLP 2019)

• What does the language of foods say about us? (Van et al., EMNLP 2019)

ACL

• Hoang Van, Ahmad Musa, Hang Chen, Stephen Kobourov, and Mihai Surdeanu. 2019. What does the language of foods say about us?. In Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019), pages 87–96, Hong Kong. Association for Computational Linguistics.