SIHCLGDec 2, 2019

Discovering Opioid Use Patterns from Social Media for Relapse Prevention

arXiv:1912.01122v11 citations
Originality Synthesis-oriented
AI Analysis

This work addresses relapse prevention for opioid addiction patients by leveraging online social media data, representing an incremental application of existing analytical techniques to a new domain.

The paper tackled the opioid crisis by analyzing social media data from Reddit to identify communication and behavior patterns in individuals with opioid use disorder, aiming to improve relapse prediction and prevention through quantitative methods like topic modeling and emotional analysis.

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 OUD. These quantitative analyses are of practical importance and demonstrate innovative ways to use information from online social media, to create technology that can assist in relapse prevention.

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