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, marvos t coils 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 chevy equinox steering wheel cover 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.