A framework for multi-faceted content analysis of social media chatter regarding non-medical use of prescription medications.

ABSTRACT:

Background

Substance use, including the non-medical use of prescription medications, is a global health problem resulting in hundreds of thousands of overdose deaths and other health problems. Social media has emerged as a potent source of information for studying substance use-related behaviours and their consequences. Mining large-scale social media data on the topic requires the development of natural language processing (NLP) and machine learning frameworks customized for this problem. Our objective in this research is to develop a framework for conducting a content analysis of Twitter chatter about the non-medical use of a set of prescription medications.

Methods

We collected Twitter data for four medications-fentanyl and morphine (opioids), alprazolam (benzodiazepine),

SUBMITTER: Raza S 

PROVIDER: S-EPMC10483682 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature