Citation

Daniulaityte R, Lamy FR, Smith GA, Nahhas RW, Carlson RG, Thirunarayan K, Martins SS, Boyer EW, Sheth A. J. Stud. Alcohol Drugs 2017; 78(6): 910-915.

Affiliation

Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis), Department of Computer Science and Engineering, Wright State University, Dayton, Ohio.

Copyright

(Copyright © 2017, Alcohol Research Documentation, Inc., Rutgers, The State University of New Jersey)

DOI

unavailable

PMID

29087826

Abstract

OBJECTIVE: Twitter data offer new possibilities for tracking health-related communications. This study is among the first to apply advanced information processing to identify geographic and content features of cannabis-related tweeting in the United States.

METHOD: Tweets were collected using streaming Application Programming Interface (March-May 2016) and were processed by eDrugTrends to identify geolocation and classify content by source (personal communication, media, retail) and sentiment (positive, negative, neutral). States were grouped by cannabis legalization policies into "recreational," "medical, less restrictive," "medical, more restrictive," and "illegal." Permutation tests were performed to analyze differences among four groups in adjusted percentages of all tweets, unique users, personal communications only, and positive-to-negative sentiment ratios.

RESULTS: About 30% of all 13,233,837 cannabis-related tweets had identifiable state-level geo-information. Among geolocated tweets, 76.2% were personal communications, 21.1% media, and 2.7% retail. About 71% of personal communication tweets expressed positive sentiment toward cannabis; 16% expressed negative sentiment. States in the recreational group had significantly greater average adjusted percentage of cannabis tweets (3.01%) compared with other groups. For personal communication tweets only, the recreational group (2.47%) was significantly greater than the medical, more restrictive (1.84%) and illegal (1.85%) groups. Similarly, the recreational group had significantly greater average positive-to-negative sentiment ratio (4.64) compared with the medical, more restrictive (4.15) and illegal (4.19) groups. Average adjusted percentages of unique users showed similar differences between recreational and other groups.

CONCLUSIONS: States with less restrictive policies displayed greater cannabis-related tweeting and conveyed more positive sentiment. The study demonstrates the potential of Twitter data to become a valuable indicator of drug-related communications in the context of varying policy environments.

Language: en