Redditors in Recovery: Text Mining Reddit to Investigate Transitions into Drug Addiction

Increasing rates of opioid drug abuse and heightened prevalence of online support communities underscore the necessity of employing data mining techniques to better understand drug addiction using these rapidly developing online resources. In this work, we obtain data from Reddit, an online collection of forums, to gather insight into drug use/misuse using text data from users themselves. Specifically, using user posts, we trained 1) a binary classifier which predicts transitions from casual drug discussion forums to drug recovery forums and 2) a Cox regression model that outputs likelihoods of such transitions. In doing so, we found that utterances of select drugs and certain linguistic features contained in one’s posts can help predict these transitions. Using unfiltered drug-related posts, our research delineates drugs that are associated with higher rates of transitions from recreational drug discussion to support/recovery discussion, offers insight into modern drug culture, and provides tools with potential applications in combating the opioid crisis.

[1]  Rosalie Liccardo Pacula,et al.  Medical marijuana laws and adolescent marijuana use in the United States: a systematic review and meta‐analysis , 2018, Addiction.

[2]  Jeffrey Heer,et al.  Forum77: An Analysis of an Online Health Forum Dedicated to Addiction Recovery , 2015, CSCW.

[3]  Peter Kreiner,et al.  The prescription opioid and heroin crisis: a public health approach to an epidemic of addiction. , 2015, Annual review of public health.

[4]  Grant T Baldwin,et al.  Relationship between Nonmedical Prescription-Opioid Use and Heroin Use. , 2016, The New England journal of medicine.

[5]  K. Tracy,et al.  Pharmacological enhancement of naltrexone treatment for opioid dependence: a review , 2011 .

[6]  Balaji Krishnapuram,et al.  On Ranking in Survival Analysis: Bounds on the Concordance Index , 2007, NIPS.

[7]  Jonathan Penm,et al.  Strategies and policies to address the opioid epidemic: A case study of Ohio , 2017, Journal of the American Pharmacists Association : JAPhA.

[8]  Rachel E. Ginn,et al.  Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter , 2016, Drug Safety.

[9]  Benjamin Fischman,et al.  Data Driven Support for Substance Addiction Recovery Communities , 2018, CHI Extended Abstracts.

[10]  Lawrence Scholl,et al.  Overdose Deaths Involving Opioids, Cocaine, and Psychostimulants — United States, 2015–2016 , 2018, MMWR. Morbidity and mortality weekly report.

[11]  S. Eysenck,et al.  A further investigation into the personality of drug addicts in treatment. , 1980, British journal of addiction.

[12]  J. Pennebaker,et al.  Psychological aspects of natural language. use: our words, our selves. , 2003, Annual review of psychology.

[13]  Dragomir R. Radev,et al.  Centroid-based summarization of multiple documents , 2004, Inf. Process. Manag..

[14]  Steven C Hayes,et al.  Reducing self-stigma in substance abuse through acceptance and commitment therapy: Model, manual development, and pilot outcomes , 2008, Addiction research & theory.

[15]  Rahul Singh,et al.  Identifying individuals amenable to drug recovery interventions through computational analysis of addiction content in social media , 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[16]  Mark Dredze,et al.  Experimenting with Drugs (and Topic Models): Multi-Dimensional Exploration of Recreational Drug Discussions , 2012, AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text.

[17]  Woo-Young Ahn,et al.  Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence. , 2016, Drug and alcohol dependence.

[18]  C. Blakemore,et al.  Development of a rational scale to assess the harm of drugs of potential misuse , 2007, The Lancet.

[19]  Quoc V. Le,et al.  Distributed Representations of Sentences and Documents , 2014, ICML.

[20]  Mark Edmund Rose,et al.  Are Prescription Opioids Driving the Opioid Crisis? Assumptions vs Facts , 2017, Pain medicine.

[21]  Jeffrey T. Hancock,et al.  Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data , 2017, Journal of medical Internet research.

[22]  Mark Dredze,et al.  Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media , 2016, CHI.

[23]  R. Bonnie,et al.  Pain Management and the Opioid Epidemic: Balancing Societal and Individual Benefits and Risks of Prescription Opioid Use , 2017 .

[24]  John Nerbonne,et al.  The Secret Life of Pronouns. What Our Words Say About Us , 2014, Lit. Linguistic Comput..

[25]  Lipika Dey,et al.  Multi-Document Summarization Using Distributed Bag-of-Words Model , 2017, 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI).

[26]  L. Baker,et al.  Internet use and stigmatized illness. , 2005, Social science & medicine.