Discovering Opioid Use Patterns from Social Media for Relapse Prevention
Zhou Yang, Spencer Bradshaw, Rattikorn Hewett, and Fang Jin

TL;DR
This paper analyzes social media data, specifically Reddit discussions, to identify behavioral patterns and emotional states of individuals with opioid use disorder, aiming to improve relapse prediction and prevention strategies.
Contribution
It introduces a novel multidisciplinary analytic approach to characterize opioid addiction behaviors from social media data, aiding in relapse prevention.
Findings
Identification of key discussion topics related to opioid use
Analysis of emotional states associated with relapse risk
Modeling of online social interactions for behavioral insights
Abstract
The United States is currently experiencing an unprecedented opioid crisis, and opioid overdose has become a leading cause of injury and death. Effective opioid addiction recovery calls for not only medical treatments, but also behavioral interventions for impacted individuals. In this paper, we study communication and behavior patterns of patients with opioid use disorder (OUD) from social media, intending to demonstrate how existing information from common activities, such as online social networking, might lead to better prediction, evaluation, and ultimately prevention of relapses. Through a multi-disciplinary and advanced novel analytic perspective, we characterize opioid addiction behavior patterns by analyzing opioid groups from Reddit.com - including modeling online discussion topics, analyzing text co-occurrence and correlations, and identifying emotional states of people with…
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Taxonomy
TopicsMental Health via Writing · Sentiment Analysis and Opinion Mining · Substance Abuse Treatment and Outcomes
