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 Long Sleeve Tops 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 NO-POO BLUE 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.