  According to NSDUH (National Survey on Drug Use and Health), 20 million
Americans consumed drugs in the past few 30 days. Combating illicit drug use is
of great interest to public health and law enforcement agencies. Despite of the
importance, most of the existing studies on drug uses rely on surveys. Surveys
on sensitive topics such as drug use may not be answered truthfully by the
people taking them. Selecting a representative sample to survey is another
major challenge. In this paper, we explore the possibility of using big
multimedia data, including both images and text, from social media in order to
discover drug use patterns at fine granularity with respect to demographics.
Instagram posts are searched and collected by drug related terms by analyzing
the hashtags supplied with each post. A large and dynamic dictionary of
frequent drug related slangs is used to find these posts. User demographics are
extracted using robust face image analysis algorithms. These posts are then
mined to find common trends with regard to the time and location they are
posted, and further in terms of age and gender of the drug users. Furthermore,
by studying the accounts followed by the users of drug related posts, we
extract common interests shared by drug users.
