ArticleApplied geography (Sevenoaks, England)2016
Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity.
Article in Applied geography (Sevenoaks, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Are green spaces healthier in spring? Examining seasonal variations in the association between urban green spaces and emotional well-being in Wuhan, China.Frontiers in public health · 2026Article
- Socioeconomic and environmental factors associated with glaucoma in an African Ancestry Population: findings from the Primary Open-Angle African American Glaucoma Genetics (POAAGG) study.Eye (London, England) · 2025Article
- Evaluating machine learning models for stroke prediction based on clinical variables.Frontiers in neurology · 2025Article
- Empowering health geography research with location-based social media data: innovative food word expansion and energy density prediction via word embedding and machine learning.International journal of health geographics · 2023Article
- Deciphering Latent Health Information in Social Media Using a Mixed-Methods Design.Healthcare (Basel, Switzerland) · 2022Article
- Spatial and sentiment analysis of public opinion toward COVID-19 pandemic using twitter data: At the early stage of vaccination.International journal of disaster risk reduction : IJDRR · 2022Article
- Diet during the COVID-19 pandemic: An analysis of Twitter data.Patterns (New York, N.Y.) · 2022Article
- Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review.Journal of medical Internet research · 2022Article
- An Evaluation of Geo-located Twitter Data for Measuring Human Migration.International journal of geographical information science : IJGIS · 2022Article
- A scoping review on the use of machine learning in research on social determinants of health: Trends and research prospects.SSM - population health · 2021Article
- Twitter-Derived Social Neighborhood Characteristics and Individual-Level Cardiometabolic Outcomes: Cross-Sectional Study in a Nationally Representative Sample.JMIR public health and surveillance · 2020Article
- Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Article
- Pride, Love, and Twitter Rants: Combining Machine Learning and Qualitative Techniques to Understand What Our Tweets Reveal about Race in the US.International journal of environmental research and public health · 2019Article
- Using social media to assess the consumer nutrition environment: comparing Yelp reviews with a direct observation audit instrument for grocery stores.Public health nutrition · 2019Article
- Twitter-based measures of neighborhood sentiment as predictors of residential population health.PloS one · 2019Article
- Twitter-derived measures of sentiment towards minorities (2015-2016) and associations with low birth weight and preterm birth in the United States.Computers in human behavior · 2018Article
- Twitter-derived neighborhood characteristics associated with obesity and diabetes.Scientific reports · 2017Article
- Geotagged US Tweets as Predictors of County-Level Health Outcomes, 2015-2016.American journal of public health · 2017Article
- Social media indicators of the food environment and state health outcomes.Public health · 2017Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
objectivesUsing publicly available, geotagged Twitter data, we created neighborhood indicators for happiness, food and physical activity for three large counties: Salt Lake, San Francisco and New York.
methodsWe utilize 2.8 million tweets collected between February-August 2015 in our analysis. Geo-coordinates of where tweets were sent allow us to spatially join them to 2010 census tract locations. We implemented quality control checks and tested associations between Twitter-derived variables and sociodemographic characteristics.
resultsFor a random subset of tweets, manually labeled tweets and algorithm labeled tweets had excellent levels of agreement: 73% for happiness; 83% for food, and 85% for physical activity. Happy tweets, healthy food references, and physical activity references were less frequent in census tracts with greater economic disadvantage and higher proportions of racial/ethnic minorities and youths.
conclusionsSocial media can be leveraged to provide greater understanding of the well-being and health behaviors of communities-information that has been previously difficult and expensive to obtain consistently across geographies. More open access neighborhood data can enable better design of programs and policies addressing social determinants of health.
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