2019
DOI: 10.1093/jamia/ocz181
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Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics

Abstract: Objective Initiatives to reduce neighborhood-based health disparities require access to meaningful, timely, and local information regarding health behavior and its determinants. We examined the validity of Twitter as a source of information for neighborhood-level analysis of dietary choices and attitudes. Materials and Methods We analyzed the “healthiness” quotient and sentiment in food-related tweets at the census tract leve… Show more

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Cited by 28 publications
(25 citation statements)
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“…We used the categories offered by Aliments du Québec, a nonfor-profit organization whose mission is to promote the local agri-food industry [65] and we complemented it with the Canada's agriculture sectors categories proposed by the Government of Canada [66]. Then, using Wikipedia, we found the English keywords related to each of these categories [67] and we added a "general" category for keyword such as "food" or "meal". Finally, each keyword was translated into French by one of the French-speaking researchers.…”
Section: Methodsmentioning
confidence: 99%
“…We used the categories offered by Aliments du Québec, a nonfor-profit organization whose mission is to promote the local agri-food industry [65] and we complemented it with the Canada's agriculture sectors categories proposed by the Government of Canada [66]. Then, using Wikipedia, we found the English keywords related to each of these categories [67] and we added a "general" category for keyword such as "food" or "meal". Finally, each keyword was translated into French by one of the French-speaking researchers.…”
Section: Methodsmentioning
confidence: 99%
“…Settings the digital food environment represented in the review mentioning food-related behavior and locations where food and drinks were consumed, and found associations between these digital activities and obesity, diabetes and hypertension rates, low fruit and vegetable consumption, higher levels of fat, cholesterol and sugar consumption, and food deserts in the physical world. [171][172][173] Some studies were able to predict food deprivation/food deserts, obesity and hypertension in the physical world using Twitter data. 172,174 As these examples show, digital and physical food environments are interconnected and influencing one another, rather than separate entities.…”
Section: Digital Food Culturementioning
confidence: 99%
“…Social media data have proved useful in predicting health outcomes in many studies; therefore, these data may prove to be a very rich source for yet another health-related issue: food insecurity. Using social media data to predict the emergence of food deserts provides a people-centered approach for identifying food deserts by allowing for the examination of the dietary consumption and habits of individuals who reside in food deserts versus those who do not reside in food deserts [ 16 ].…”
Section: Introductionmentioning
confidence: 99%