“How Did We Get Here?”: Topic Drift in Online Health Discussions

Journals

1. Zhou J, Wang G, Zhou T, Fan T. The role of off-topic discussions in online health support groups: insights from a content analysis of an online rectal cancer group. Supportive Care in Cancer 2020;28(7):3219 View
2. Park A, Conway M. Longitudinal Changes in Psychological States in Online Health Community Members: Understanding the Long-Term Effects of Participating in an Online Depression Community. Journal of Medical Internet Research 2017;19(3):e71 View
3. Dechesne M, Bandt-Law B. Terror in time: extending culturomics to address basic terror management mechanisms. Cognition and Emotion 2019;33(3):492 View
4. Bopp T, Stellefson M. Practical and Ethical Considerations for Schools Using Social Media to Promote Physical Literacy in Youth. International Journal of Environmental Research and Public Health 2020;17(4):1225 View
5. Bender J, Flora P, Milosevic E, Soheilipour S, Maharaj N, Dirlea M, Parvin L, Matthew A, Kazanjian A. Training prostate cancer survivors and caregivers to be peer navigators: a blended online/in-person competency-based training program. Supportive Care in Cancer 2021;29(3):1235 View
6. Park A, Conway M, Chen A. Examining thematic similarity, difference, and membership in three online mental health communities from reddit: A text mining and visualization approach. Computers in Human Behavior 2018;78:98 View
7. Zhao D, Zhang Q, Ma F. Communication that changes lives: an exploratory research on a Chinese online hypertension community. Library Hi Tech 2020;38(4):883 View
8. Park A, Conway M. Harnessing Reddit to Understand the Written-Communication Challenges Experienced by Individuals With Mental Health Disorders: Analysis of Texts From Mental Health Communities. Journal of Medical Internet Research 2018;20(4):e121 View
9. Canter K, Christofferson J, Scialla M, Kazak A. Technology-Focused Family Interventions in Pediatric Chronic Illness: A Systematic Review. Journal of Clinical Psychology in Medical Settings 2019;26(1):68 View
10. Sun Y, Kolacinski R, Loparo K. Transitive Topic Modeling with Conversational Structure Context: Discovering Topics that are Most Popular in Online Discussions. International Journal of Semantic Computing 2020;14(02):273 View
11. Sun H, Fichman P. Evolution of discussion topics on an online depression self-help group. Library Hi Tech 2023 View
12. De Santo A, Moro A, Kocher B, Holzer A. Helping Each Other Quit Online: Understanding User Engagement and Real Life Outcomes of the r/StopSmoking Digital Smoking Cessation Community. ACM Transactions on Social Computing 2022 View
13. Hu M, Benson R, Chen A, Zhu S, Conway M. Determining the prevalence of cannabis, tobacco, and vaping device mentions in online communities using natural language processing. Drug and Alcohol Dependence 2021;228:109016 View
14. Benson R, Hu M, Chen A, Zhu S, Conway M. Examining Cannabis, Tobacco, and Vaping Discourse on Reddit: An Exploratory Approach Using Natural Language Processing. Frontiers in Public Health 2022;9 View
15. Ye P, Liu L. Factors Affecting User Intention to Pay via Online Medical Service Platform. International Journal of Healthcare Information Systems and Informatics 2022;16(4):1 View
16. Oduru T, Jordan A, Park A. Healthy vs. Unhealthy Food Images: Image Classification of Twitter Images. International Journal of Environmental Research and Public Health 2022;19(2):923 View
17. Zhang J, Pan Y, Lin H, Sun Z, Wu P, Tu J. Infodemic: Challenges and solutions in topic discovery and data process. Archives of Public Health 2023;81(1) View
18. Liu J, Jiang H, Wang S. Physicians’ Online Writing Language Style and Patient Satisfaction: The Mediator of Depth of Physician–Patient Interactions. Healthcare 2023;11(11):1569 View

Books/Policy Documents

1. Alshehri J, Stanojevic M, Dragut E, Obradovic Z. Advances in Information Retrieval. View