HashtagHealth

About HashtagHealth

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 Epidemiology and Biostatistics at the University of Maryland. 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.

Publications

Nguyen, T. T., Meng, H. W., Sandeep, S., McCullough, M., Yu, W., Lau, Y., ... & Nguyen, Q. C. (2018). 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, 89, 308-315. doi:10.1016/j.chb.2018.08.010

Nguyen, Q. C., Sajjadi, M., McCullough, M., Pham, M., Nguyen, T. T., Yu, W., ... & Brunisholz, K. (2018). Neighbourhood looking glass: 360º automated characterisation of the built environment for neighbourhood effects research. J Epidemiol Community Health, jech-2017. doi:10.1136/jech-2017-209456

Nguyen, Q. C., Brunisholz, K. D., Yu, W., McCullough, M., Hanson, H. A., Litchman, M. L., . . . Smith, K. R. (2017). Twitter-derived neighborhood characteristics associated with obesity and diabetes. Scientific Reports, 7(1), 16425. doi:10.1038/s41598-017-16573-1

Meng, H.-W., Kath, S., Li, D., & Nguyen, Q. C. (2017). National substance use patterns on Twitter. PLOS ONE, 12(11), e0187691. doi:10.1371/journal.pone.0187691

Nguyen, Q. C., McCullough, M., Meng, H. W., Paul, D., Li, D., Kath, S., ... & Li, F. (2017). Geotagged US Tweets as Predictors of County-Level Health Outcomes, 2015–2016. American Journal of Public Health, (0), e1-e7. doi: 10.2105/AJPH.2017.303993

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: 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: 10.1016/j.apgeog.2016.06.003

Portfolio

HashtagHealth Poster

Census tract level food data (2015-2018)

Download (xlsx)

State Level Analysis Maps

County Level Analysis Map

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.

People

Faculty

Dr. Quynh Nguyen (Principal Investigator), Assistant Professor, Department of Epidemiology and Biostatistics, University of Maryland, 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

Research Assistants

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

Alumni

Suraj Kath, Software Engineer, Google

Dapeng Li, Assistant Professor, South Dakota State University

Address:

Dept. of Epidemiology and Biostatistics
2234B School of Public Health Building
4200 Valley Dr #2242, College Park, MD 2074-22611