Literature DB >> 32202005

Detecting illicit opioid content on Twitter.

Babak Tofighi1,2, Yindalon Aphinyanaphongs1,3, Christina Marini1, Shouron Ghassemlou4, Peyman Nayebvali1, Isabel Metzger3, Ananditha Raghunath3, Shailin Thomas1.   

Abstract

INTRODUCTION AND AIMS: This article examines the feasibility of leveraging Twitter to detect posts authored by people who use opioids (PWUO) or content related to opioid use disorder (OUD), and manually develop a multidimensional taxonomy of relevant tweets. DESIGN AND METHODS: Twitter messages were collected between June and October 2017 (n = 23 827) and evaluated using an inductive coding approach. Content was then manually classified into two axes (n = 17 420): (i) user experience regarding accessing, using, or recovery from illicit opioids; and (ii) content categories (e.g. policies, medical information, jokes/sarcasm).
RESULTS: The most prevalent categories consisted of jokes or sarcastic comments pertaining to OUD, PWUOs or hypothetically using illicit opioids (63%), informational content about treatments for OUD, overdose prevention or accessing self-help groups (20%), and commentary about government opioid policy or news related to opioids (17%). Posts by PWUOs centered on identifying illicit sources for procuring opioids (i.e. online, drug dealers; 49%), symptoms and/or strategies to quell opioid withdrawal symptoms (21%), and combining illicit opioid use with other substances, such as cocaine or benzodiazepines (17%). State and public health experts infrequently posted content pertaining to OUD (1%). DISCUSSION AND
CONCLUSIONS: Twitter offers a feasible approach to identify PWUO. Further research is needed to evaluate the efficacy of Twitter to disseminate evidence-based content and facilitate linkage to treatment and harm reduction services.
© 2020 Australasian Professional Society on Alcohol and other Drugs.

Entities:  

Keywords:  Twitter messaging; opioid use disorder; social media

Mesh:

Substances:

Year:  2020        PMID: 32202005      PMCID: PMC8276110          DOI: 10.1111/dar.13048

Source DB:  PubMed          Journal:  Drug Alcohol Rev        ISSN: 0959-5236


  9 in total

1.  A content analysis of chronic diseases social groups on Facebook and Twitter.

Authors:  Isabel De la Torre-Díez; Francisco Javier Díaz-Pernas; Míriam Antón-Rodríguez
Journal:  Telemed J E Health       Date:  2012-05-31       Impact factor: 3.536

Review 2.  Twitter as a Tool for Health Research: A Systematic Review.

Authors:  Lauren Sinnenberg; Alison M Buttenheim; Kevin Padrez; Christina Mancheno; Lyle Ungar; Raina M Merchant
Journal:  Am J Public Health       Date:  2016-11-17       Impact factor: 9.308

3.  Technology Use Patterns Among Patients Enrolled in Inpatient Detoxification Treatment.

Authors:  Babak Tofighi; Noelle Leonard; Peter Greco; Aboozar Hadavand; Michelle C Acosta; Joshua D Lee
Journal:  J Addict Med       Date:  2019 Jul/Aug       Impact factor: 3.702

4.  Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media.

Authors:  Michael Chary; Nicholas Genes; Christophe Giraud-Carrier; Carl Hanson; Lewis S Nelson; Alex F Manini
Journal:  J Med Toxicol       Date:  2017-08-22

5.  Prevalence of Marijuana-Related Traffic on Twitter, 2012-2013: A Content Analysis.

Authors:  Leah Thompson; Frederick P Rivara; Jennifer M Whitehill
Journal:  Cyberpsychol Behav Soc Netw       Date:  2015-06

6.  Twitter-Based Detection of Illegal Online Sale of Prescription Opioid.

Authors:  Tim K Mackey; Janani Kalyanam; Takeo Katsuki; Gert Lanckriet
Journal:  Am J Public Health       Date:  2017-10-19       Impact factor: 9.308

7.  Exploring trends of nonmedical use of prescription drugs and polydrug abuse in the Twittersphere using unsupervised machine learning.

Authors:  Janani Kalyanam; Takeo Katsuki; Gert R G Lanckriet; Tim K Mackey
Journal:  Addict Behav       Date:  2016-08-17       Impact factor: 3.913

8.  Tweaking and tweeting: exploring Twitter for nonmedical use of a psychostimulant drug (Adderall) among college students.

Authors:  Carl L Hanson; Scott H Burton; Christophe Giraud-Carrier; Josh H West; Michael D Barnes; Bret Hansen
Journal:  J Med Internet Res       Date:  2013-04-17       Impact factor: 5.428

9.  Using twitter to examine smoking behavior and perceptions of emerging tobacco products.

Authors:  Mark Myslín; Shu-Hong Zhu; Wendy Chapman; Mike Conway
Journal:  J Med Internet Res       Date:  2013-08-29       Impact factor: 5.428

  9 in total
  3 in total

1.  Assessing perceptions about medications for opioid use disorder and Naloxone on Twitter.

Authors:  Babak Tofighi; Omar El Shahawy; Andrew Segoshi; Katerine P Moreno; Beita Badiei; Abeed Sarker; Noa Krawczyk
Journal:  J Addict Dis       Date:  2020-08-24

2.  Harm reduction via online platforms for people who use drugs in Russia: A qualitative analysis of web outreach work.

Authors:  Arsen Davitadze; Peter Meylakhs; Aleksey Lakhov; Elizabeth J King
Journal:  Res Sq       Date:  2020-09-15

3.  Harm reduction via online platforms for people who use drugs in Russia: a qualitative analysis of web outreach work.

Authors:  Arsen Davitadze; Peter Meylakhs; Aleksey Lakhov; Elizabeth J King
Journal:  Harm Reduct J       Date:  2020-12-09
  3 in total

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