Cannabis remains one of the most commonly used psychoactive substances in the U.S., and current changes in legalization policy indicate broadening acceptability. At the same time, substance abusers have sought similar, or more enhanced highs, through use of synthetic cannabinoids, new designer drugs with constantly changing chemical formulations that have been linked to adverse health effects and present significant challenges to public health. Submitted in response to NIDA RFA-CA-14-008 (Research Area 1), this multi-PI study builds on multidisciplinary collaboration between the researchers in the Center for Interventions, Treatment, and Addictions Research, and the Ohio Center of Excellence in Knowledge-enabled Computing at Wright State University to develop an innovative software platform, eDrugTrends, that will facilitate analysis of trends in knowledge, attitudes, and behaviors related to the use of cannabis and synthetic cannabinoids as discussed on Web forums and Twitter. To date, no one has developed a computer platform capable of collecting and semi-automatically analyzing data from these two complementary social media sources. We will build on the existing infrastructure developed by our interdisciplinary research team: Twitris, a robust and highly scalable platform designed to analyze Twitter data, and PREDOSE, a platform developed for our collaborative NIH grant (R21 DA030571) to analyze Web forum data on illegal buprenorphine use. Key elements of Twitris and PREDOSE will be adapted and enhanced using Semantic Web, Natural Language Processing, and Machine Learning techniques to advance the analysis of social media data for drug abuse research and is thus maximally responsive to the RFA.
The Specific Aims are to: 1) Develop a comprehensive software platform, eDrugTrends, for semi-automated processing and visualization of thematic, sentiment, spatio-temporal, and social network dimensions of social media data (Twitter and Web forums) on cannabis and synthetic cannabinoid use. 2) Deploy eDrugTrends to: a) Identify and compare trends in knowledge, attitudes, and behaviors related to cannabis and synthetic cannabinoid use across U.S. regions with different cannabis legalization policies using Twitter and Web forum data. b) Analyze social network characteristics and identify key influencers (opinions leaders) in cannabis and synthetic cannabinoid-related discussions on Twitter. The development of eDrugTrends will advance the field's technological and methodological capabilities, and our deployment of the platform will inform the field on new trends regarding the use of cannabis, synthetic cannabinoids and other drugs. eDrugTrends will have high public health impact by providing a tool that can be used to inform more timely interventions and policy responses to changes in cannabis and synthetic cannabinoid use and associated harms.

Public Health Relevance

Building on inter-disciplinary collaboration between substance abuse researchers and computer scientists, we will develop and deploy an innovative software platform, eDrugTrends, to facilitate analysis of Twitter and Web forum data on cannabis and synthetic cannabinoid use. The study will contribute to the advancement of social media surveillance methods to improve public health, and it will provide timely information on emerging trends in the context of changing cannabis laws in the U.S. that can ultimately be used to inform interventions and policy.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA039454-03
Application #
9112982
Study Section
Special Emphasis Panel (ZCA1-SRB-H (O1))
Program Officer
Obrien, Moira
Project Start
2014-08-15
Project End
2017-07-31
Budget Start
2016-08-01
Budget End
2017-07-31
Support Year
3
Fiscal Year
2016
Total Cost
$460,736
Indirect Cost
$128,336
Name
Wright State University
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
047814256
City
Dayton
State
OH
Country
United States
Zip Code
45435
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Lamy, Francois R; Daniulaityte, Raminta; Zatreh, Mussah et al. (2018) ""You got to love rosin: Solventless dabs, pure, clean, natural medicine."" Exploring Twitter data on emerging trends in Rosin Tech marijuana concentrates. Drug Alcohol Depend 183:248-252
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Daniulaityte, Raminta; Chen, Lu; Lamy, Francois R et al. (2016) ""When 'Bad' is 'Good'"": Identifying Personal Communication and Sentiment in Drug-Related Tweets. JMIR Public Health Surveill 2:e162
Daniulaityte, Raminta; Nahhas, Ramzi W; Wijeratne, Sanjaya et al. (2015) ""Time for dabs"": Analyzing Twitter data on marijuana concentrates across the U.S. Drug Alcohol Depend 155:307-11

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