Literature DB >> 26364675

Drug Use in the Twittersphere: A Qualitative Contextual Analysis of Tweets About Prescription Drugs.

Lukas Shutler1, Lewis S Nelson2, Ian Portelli2, Courtney Blachford3, Jeanmarie Perrone4.   

Abstract

Tweets about prescription opioid use may reveal insights into the prescription drug epidemic. We qualitatively assessed 2,100 tweets about prescription opioids utilizing a Twitter Archiving Google Spreadsheet® and determined whether the tweet represented: abuse (i.e., use to get high), not abuse (i.e., use as analgesic), or was not characterizable (e.g., "I need a Percocet") and whether the connotation was positive (i.e. promote psychoactive or analgesic use), negative (i.e., adverse event), or not characterizable. Abuse was commonly described and the majority of terms (>66%) represented a positive connotation. Twitter can be a resource to observe trends in perceptions about prescription opioid use.

Entities:  

Keywords:  Twitter; prescription drug abuse; toxicovigilance

Mesh:

Substances:

Year:  2015        PMID: 26364675     DOI: 10.1080/10550887.2015.1074505

Source DB:  PubMed          Journal:  J Addict Dis        ISSN: 1055-0887


  20 in total

1.  Social Media Listening for Routine Post-Marketing Safety Surveillance.

Authors:  Gregory E Powell; Harry A Seifert; Tjark Reblin; Phil J Burstein; James Blowers; J Alan Menius; Jeffery L Painter; Michele Thomas; Carrie E Pierce; Harold W Rodriguez; John S Brownstein; Clark C Freifeld; Heidi G Bell; Nabarun Dasgupta
Journal:  Drug Saf       Date:  2016-05       Impact factor: 5.606

2.  Mining Social Media Data for Biomedical Signals and Health-Related Behavior.

Authors:  Rion Brattig Correia; Ian B Wood; Johan Bollen; Luis M Rocha
Journal:  Annu Rev Biomed Data Sci       Date:  2020-05-04

Review 3.  Integrating Personalized Technology in Toxicology: Sensors, Smart Glass, and Social Media Applications in Toxicology Research.

Authors:  Stephanie Carreiro; Peter R Chai; Jennifer Carey; Brittany Chapman; Edward W Boyer
Journal:  J Med Toxicol       Date:  2017-04-12

4.  "Retweet to Pass the Blunt": Analyzing Geographic and Content Features of Cannabis-Related Tweeting Across the United States.

Authors:  Raminta Daniulaityte; Francois R Lamy; G Alan Smith; Ramzi W Nahhas; Robert G Carlson; Krishnaprasad Thirunarayan; Silvia S Martins; Edward W Boyer; Amit Sheth
Journal:  J Stud Alcohol Drugs       Date:  2017-11       Impact factor: 2.582

Review 5.  Capturing the Patient's Perspective: a Review of Advances in Natural Language Processing of Health-Related Text.

Authors:  G Gonzalez-Hernandez; A Sarker; K O'Connor; G Savova
Journal:  Yearb Med Inform       Date:  2017-09-11

6.  Towards Automating Location-Specific Opioid Toxicosurveillance from Twitter via Data Science Methods.

Authors:  Abeed Sarker; Graciela Gonzalez-Hernandez; Jeanmarie Perrone
Journal:  Stud Health Technol Inform       Date:  2019-08-21

7.  Posting, texting, and related social risk behavior while high.

Authors:  Joseph J Palamar; Austin Le; Patricia Acosta
Journal:  Subst Abus       Date:  2019-08-05       Impact factor: 3.716

8.  "When 'Bad' is 'Good'": Identifying Personal Communication and Sentiment in Drug-Related Tweets.

Authors:  Raminta Daniulaityte; Lu Chen; Francois R Lamy; Robert G Carlson; Krishnaprasad Thirunarayan; Amit Sheth
Journal:  JMIR Public Health Surveill       Date:  2016-10-24

9.  Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter.

Authors:  Abeed Sarker; Karen O'Connor; Rachel Ginn; Matthew Scotch; Karen Smith; Dan Malone; Graciela Gonzalez
Journal:  Drug Saf       Date:  2016-03       Impact factor: 5.606

10.  Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data.

Authors:  Takeo Katsuki; Tim Ken Mackey; Raphael Cuomo
Journal:  J Med Internet Res       Date:  2015-12-16       Impact factor: 5.428

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