Utilizing Big Data and Twitter to Discover Emergent Online Communities of Cannabis Users
Baumgartner, P., & Peiper, N. (2017). Utilizing Big Data and Twitter to Discover Emergent Online Communities of Cannabis Users. Substance Abuse: Research and Treatment, 11, 1-9. DOI: 10.1177/1178221817711425
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.