Current Projects and Publications
Low, E., Monsen, J., Schow, L., Roberts, R., Collins, L., Johnson, H., Hanson, C.L., Snell, Q., & Tass, S.E. (2024). Predicting bullying victimization among adolescents using the risk and protective factor framework: A large-scale machine learning approach. BMC Public Health. (In Review)
Ke, S.Y., Neeley-Tass, E.S., Barnes, M.D., Hanson, C.L., & Snell, Q. (2022). COVID-19 health beliefs regarding mask-wearing and vaccinations on twitter: A deep learning approach. JMIR Infodemiology, 2(2), e37861. https://doi.org/10.2196/37861
Weller, O., Sagers, L., Hanson, C.L., Snell, Q., Tass, S., & Barnes, M.D. (2021). Predicting suicidal thoughts and behavior among adolescents using the risk and protective factor framework: A large scale machine learning approach. Plos One, 16(11), e0258535. https://doi.org/10.1371/journal.pone.0258535
Barnes, M., Hanson, C.L., & Giraud-Carrier, C. (2018). The case for computational health science. Healthcare Informatics Research, 2(1), 99-110. https://doi.org/10.1007/s41666-018-0024-y
Chary, M., Genes, N., Giraud-Carrier, C., Hanson, C.L., Nelson, A.F., & Manini, A.F. (2017). Estimating prescription drug misuse from Twitter. Journal of Medical Toxicology, 13(40), 278-286. https://doi.org/10.1007/s13181-017-0625-5
Jashinsky, J., Magnusson, B., Hanson, C.L., & Barnes, M. (2017). Media agenda setting regarding gun violence before and after a mass shooting. Frontiers in Public Health, 4, 291. https://doi.org/10.3389/fpubh.2016.00291
Braithwaite, S.R., Giraud-Carrier, C., West, J., Barnes, M. & Hanson, C.L. (2016). Validating machine learning algorithms for Twitter data against established measures of suicidality. JMIR Mental Health, 3(2), e21. http://doi.org/10.2196/mental.4822
Hanson, C.L., Cannon, B., Burton, S., Giraud-Carrier, C. (2013). An exploration of social circles and prescription drug abuse through Twitter. Journal of Medical Internet Research, 15(9), e189. https://doi.org/10.2196/jmir.2741
Hanson, C.L., Burton, S., Giraud-Carrier, C., West, J., Barnes, M., & Hansen, B., (2013). Tweaking and tweeting: Exploring Twitter for non-medical use of Adderall among college students. Journal of Medical Internet Research, 15(4), e62. https://doi.org/10.2196/jmir.2503
Jashinsky, J., Burton, S., Hanson, C.L., West, J., Giraud-Carrier, C., Barnes, M., & Argyle, T. (2013). Tracking suicide risk factors through Twitter in the U.S. Journal of Crisis Intervention and Suicide Prevention, 1-7. https://doi.org/10.1027/0227-5910/a000234
West, J., Hall, P., Hanson, C.L., Barnes, M.D., Giraud-Carrier, C., & Barrett, J. (2012). There’s an app for that: Content analysis of iTune’s health care and fitness apps. Journal of Medical Internet Research, 14(3), e72. https://doi.org/10.2196/jmir.1977
West, J.H., Hall, C.P., Hanson, C.L., Prier, K., Giraud-Carrier, C., Neeley, E.S., & Barnes, M.D. (2012). Temporal variability of problem drinking on Twitter. Open Journal of Preventive Medicine, 2(1). https://doi.org/10.4236/ojpm.2012.21007
Burton, S., Morris, R., Dimond, M. Hansen, J. Giraud-Carrier, C., West, J., Hanson, C.L., & Barnes, M.D. (2012). Public health community mining in YouTube. Proceedings of the International Health Informatics Symposium, 81-90. https://doi.org/10.1145/2110363.2110376
Prier, K.W., Smith, M.S., Giraud-Carrier, C., & Hanson, C.L. (2011). Identifying health related topics on twitter: An exploration of tobacco-related tweets as a test topic. Proceedings of the 4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, 18–25. https://doi.org/10.1007/978-3-642-19656-0_4