Published on in Vol 8, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34285, first published .
Using Social Media to Predict Food Deserts in the United States: Infodemiology Study of Tweets

Using Social Media to Predict Food Deserts in the United States: Infodemiology Study of Tweets

Using Social Media to Predict Food Deserts in the United States: Infodemiology Study of Tweets

Journals

  1. Tanoh V, Hashemi-Beni L. Spatial Analysis of Socioeconomic Factors Contributing to Food Desert in North Carolina. Sustainability 2023;15(10):7848 View
  2. An R, Wang X. Artificial Intelligence Applications to Public Health Nutrition. Nutrients 2023;15(19):4285 View
  3. Luca M, Campedelli G, Centellegher S, Tizzoni M, Lepri B. Crime, inequality and public health: a survey of emerging trends in urban data science. Frontiers in Big Data 2023;6 View
  4. Sigalo N, Frias-Martinez V. Using COVID-19 Vaccine Attitudes Found in Tweets to Predict Vaccine Perceptions in Traditional Surveys: Infodemiology Study. JMIR Infodemiology 2023;3:e43700 View
  5. Molenaar A, Lukose D, Brennan L, Jenkins E, McCaffrey T. Using Natural Language Processing to Explore Social Media Opinions on Food Security: Sentiment Analysis and Topic Modeling Study. Journal of Medical Internet Research 2024;26:e47826 View
  6. Bartelmeß T, Schönfeld M, Pfeffer J. Exploring food poverty experiences in the German Twitter-Sphere. BMC Public Health 2024;24(1) View