Discovering opioid use patterns from social media for relapse prevention

Zhou Yang, Spencer Bradshaw, Rattikorn Hewett, Fang Jin

Research output: Contribution to journalArticlepeer-review


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 - 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.

Original languageEnglish
JournalUnknown Journal
StatePublished - Dec 2 2019


  • Addiction Network
  • Addiction Patterns
  • Addiction Treatment
  • Addiction on Social Media
  • Opioid Crisis
  • Opioid Use Disorder
  • Relapse Emotion

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