ArticleSubstance abuse : research and treatment2017
Utilizing Big Data and Twitter to Discover Emergent Online Communities of Cannabis Users.
Article in Substance abuse : research and treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Linguistic Methodologies to Surveil the Leading Causes of Mortality: Scoping Review of Twitter for Public Health Data.Journal of medical Internet research · 2023Article
- A Content Analysis of Social Media Discussions on THC-O-Acetate.Cannabis (Albuquerque, N.M.) · 2023Article
- Using Social Media for Clinical Research: Recommendations and Examples From the Brown-Lifespan Center for Digital Health.Journal of medical Internet research · 2022Article
- Social Medicine: Twitter in Healthcare.Journal of clinical medicine · 2018Review
- Studying Cannabis Use Behaviors With Facebook and Web Surveys: Methods and Insights.JMIR public health and surveillance · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large shifts in medical, recreational, and illicit cannabis consumption in the United States have implications for personalizing treatment and prevention programs to a wide variety of populations. As such, considerable research has investigated clinical presentations of cannabis users in clinical and population-based samples. Studies leveraging big data, social media, and social network analysis have emerged as a promising mechanism to generate timely insights that can inform treatment and prevention research. This study extends a novel method called stochastic block modeling to derive communities of cannabis consumers as part of a complex social network on Twitter. A set of examples illustrate how this method can ascertain candidate samples of medical, recreational, and illicit cannabis users. Implications for research planning, intervention design, and public health surveillance are discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.