This paper is in the following e-collection/theme issue:

Public (e)Health (448) Machine Learning (1121) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1400) Instruments and Questionnaires for Nutrition and Food Intake (148) Infodemiology and Infoveillance (1125) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (922) Food Sciences and Nutrition Engineering (44) Innovations and Technology for Healthy Eating Education (352)

Published on in Vol 24 , No 12 (2022) :December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39340, first published .
A Novel Approach to Characterize State-level Food Environment and Predict Obesity Rate Using Social Media Data: Correlational Study

A Novel Approach to Characterize State-level Food Environment and Predict Obesity Rate Using Social Media Data: Correlational Study

A Novel Approach to Characterize State-level Food Environment and Predict Obesity Rate Using Social Media Data: Correlational Study

Authors of this article:

Chuqin Li 1 Author Orcid Image ;   Alexis Jordan 1 Author Orcid Image ;   Jun Song 2 Author Orcid Image ;   Yaorong Ge 1 Author Orcid Image ;   Albert Park 1 Author Orcid Image
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