HashtagHealth is a project funded by the National Institute of Health's (NIH) Big Data to Knowledge Initiative as a Mentored Research Career Development Award
for Dr. Quynh Nguyen
in the Department of Health, Recreation and Kinesiology at the University of Utah.
This project proposes to design and develop a new resource, HashtagHealth,
that addresses both the dearth of neighborhood data and offers novel characterizations of neighborhoods.
We will build the data algorithms and infrastructure to harness relatively untapped, cost efficient,
and pervasive social media data to develop neighborhood indicators such as food themes, healthiness of food mentions,
frequency of exercise/recreation mentions, metabolic intensity of physical activities, and happiness levels.
The specific research aims are as follows:
Aim 1. Develop a neighborhood data resource, HashtagHealth, for public health researchers.
Aim 2. Develop Big Data techniques to produce novel neighborhood indicators.
Aim 3. Utilize HashtagHealth and individual-level data from the Utah Population Database to investigate neighborhood influences on obesity among young adults.
Nguyen, Q. C., Meng, H., Li, D., Kath, S., McCullough, M., Paul, D., Kanokvimankul, P., Nguyen, T. X., & Li, F. (2017). Social media indicators of the food environment and state health outcomes. Public Health, 148, 120-128. doi: https://doi.org/10.1016/j.puhe.2017.03.013
Nguyen, Q., Li, D., Meng, H., Kath, S., Nsoesie, E., Wen, M., & Li, F. (2016). Building a national neighborhood dataset from geotagged Twitter data for indicators of happiness, diet, and physical activity. JMIR Public Health & Surveillance, Vol 2, No 2, doi: https://publichealth.jmir.org/2016/2/e158/
Nguyen, Q. C., Kath, S., Meng, H.-W., Li, D., Smith, K. R., VanDerslice, J. A., Wen, M., & Li, F. (2016). Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity. Applied Geography, 73, 77-88. doi: http://dx.doi.org/10.1016/j.apgeog.2016.06.003
This online mapping application may be used to look up Twitter characteristics as predictors of health outcomes at the county level. In the map, the variables are standardized with a mean of 0 and a standard deviation of 1. Negative values indicate below average values for a certain metric (e.g., happiness). Positive values indicate higher than average values. *Twitter data collection period: April 2015– March 2016. County summaries were derived from 80 million tweets from the contiguous United States. Map was built with Carto and Google Maps.
Dr. Quynh Nguyen (Principal Investigator), Assistant Professor, Department of Health Promotion and Education, University of Utah, USA
Dr. Ken R. Smith, Professor, Department of Family and Consumer Studies, University of Utah, USA
Dr. James A. VanDerslice, Research Associate Professor, Department of Family and Preventive Medicine, School of Medicine, University of Utah, USA
Dr. Ming Wen, Professor, Department of Sociology, University of Utah, USA
Dr. Feifei Li, Associate Professor, School of Computing, University of Utah, USA
Hsien-Wen (Sherry) Meng, Ph.D. Student, Department of Health Promotion and Education, University of Utah, USA
Matt McCullough, Ph.D. Student, Department of Geography, University of Utah, USA
Debjoyti Paul, Ph.D. student, School of Computing, University of Utah, USA
Suraj Kath, Software Engineer, Google
Dapeng Li, Postdoctoral Researcher, Michigan State University
Department of Health Promotion and Education
1901 E. So Campus, Annex B, Rm 2124, Salt Lake City, UT 84112