Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis.

Journal: Journal of medical Internet research
PMID: 40360163

Abstract

BACKGROUND: The opioid epidemic in the United States remains a major public health concern, with opioid-related deaths increasing more than 8-fold since 1999. Chronic pain, affecting 1 in 5 US adults, is a key contributor to opioid use and misuse. While previous research has explored clinical and behavioral predictors of opioid risk, less attention has been given to large-scale linguistic patterns in public discussions of pain. Social media platforms such as X (formerly Twitter) offer real-time, population-level insights into how individuals express pain, distress, and coping strategies. Understanding these linguistic markers matters because they can reveal underlying psychological states, perceptions of health care access, and community-level opioid risk factors, offering new opportunities for early detection and targeted public health response.

Authors

  • ShinYe Kim
    Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, United States.
  • Winson Fu Zun Yang
    Department of Psychiatry, Massachusetts General Hospital, Cambridge, MA, United States.
  • Zishan Jiwani
    Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, United States.
  • Emily Hamm
    Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, United States.
  • Shreya Singh
    Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, United States.

Keywords

External Resources

Popular Topics
Recent Journals