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Geotagged US Tweets as Predictors of County-Level Health Outcomes, 2015-2016
Quynh C Nguyen1, Matt McCullough1, Hsien-Wen Meng1
1Quynh C. Nguyen is with the Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park. Hsien-wen Meng and Geoffrey Loomis are with the Department of Health, Kinesiology, and Recreation; University of Utah College of Health; Salt Lake City. Matt McCullough and Dapeng Li are with the Department of Geography, University of Utah. Debjyoti Paul, Suraj Kath, and Feifei Li are with the School of Computing, University of Utah. Elaine O. Nsoesie is with Institute for Health Metrics and Evaluation, University of Washington, Seattle. Ming Wen is with the Department of Sociology, University of Utah. Ken R. Smith is with the Department of Family and Consumer Studies and Population Science, Huntsman Cancer Institute, University of Utah.
Objectives:
To leverage geotagged Twitter data to create national indicators of the social environment, with small-area indicators of prevalent sentiment and social modeling of health behaviors, and to test associations with county-level health outcomes, while controlling for demographic characteristics.
Methods:
We used Twitter's streaming application programming interface to continuously collect a random 1% subset of publicly available geo-located tweets in the contiguous United States. We collected approximately 80 million geotagged tweets from 603 363 unique Twitter users in a 12-month period (April 2015-March 2016).
Results:
Across 3135 US counties, Twitter indicators of happiness, food, and physical activity were associated with lower premature mortality, obesity, and physical inactivity. Alcohol-use tweets predicted higher alcohol-use-related mortality.
Conclusions:
Social media represents a new type of real-time data that may enable public health officials to examine movement of norms, sentiment, and behaviors that may portend emerging issues or outbreaks-thus providing a way to intervene to prevent adverse health events and measure the impact of health interventions.