Large-scale social media language analysis reveals emotions and behaviours associated with nonmedical prescription drug use

Abstract

AbstractNonmedical use of prescription drugs (NMPDU) is a global health concern. The extent of, behaviors and emotions associated with, and reasons for NMPDU are not well-captured through traditional instruments such as surveys, prescribing databases and insurance claims. Therefore, this study analyses ∼130 million public posts from 87,718 Twitter users in terms of expressed emotions, sentiments, concerns, and potential reasons for NMPDU via natural language processing. Our results show that users in the NMPDU group express more negative emotions and less positive emotions, more concerns about family, the past and body, and less concerns related to work, leisure, home, money, religion, health and achievement, compared to a control group (i.e., users who never reported NMPDU). NMPDU posts tend to be highly polarized, indicating potential emotional triggers. Gender-specific analysis shows that female users in the NMPDU group express more content related to positive emotions, anticipation, sadness, joy, concerns about family, friends, home, health and the past, and less about anger, compared to males. The findings of the study can enrich our understanding of NMPDU.