  With 93% of pro-marijuana population in US favoring legalization of medical
marijuana, high expectations of a greater return for Marijuana stocks, and
public actively sharing information about medical, recreational and business
aspects related to marijuana, it is no surprise that marijuana culture is
thriving on Twitter. After the legalization of marijuana for recreational and
medical purposes in 29 states, there has been a dramatic increase in the volume
of drug-related communication on Twitter. Specifically, Twitter accounts have
been established for promotional and informational purposes, some prominent
among them being American Ganja, Medical Marijuana Exchange, and Cannabis Now.
Identification and characterization of different user types can allow us to
conduct more fine-grained spatiotemporal analysis to identify dominant or
emerging topics in the echo chambers of marijuana-related communities on
Twitter. In this research, we mainly focus on classifying Twitter accounts
created and run by ordinary users, retailers, and informed agencies.
Classifying user accounts by type can enable better capturing and highlighting
of aspects such as trending topics, business profiling of marijuana companies,
and state-specific marijuana policymaking. Furthermore, type-based analysis can
provide more profound understanding and reliable assessment of the implications
of marijuana-related communications. We developed a comprehensive approach to
classifying users by their types on Twitter through contextualization of their
marijuana-related conversations. We accomplished this using compositional
multiview embedding synthesized from People, Content, and Network views
achieving 8% improvement over the empirical baseline.
