  Drug use by people is on the rise and is of great interest to public health
agencies and law enforcement agencies. As found by the National Survey on Drug
Use and Health, 20 million Americans aged 12 years or older consumed illicit
drugs in the past few 30 days. Given their ubiquity in everyday life, drug
abuse related studies have received much and constant attention. However, most
of the existing studies rely on surveys. Surveys present a fair number of
problems because of their nature. Surveys on sensitive topics such as illicit
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 data from social media in order to
understand illicit drug use behaviors. Instagram posts are collected using drug
related terms by analyzing the hashtags supplied with each post. A large and
dynamic dictionary of frequent illicit drug related slang is used to find these
posts. These posts are studied to find common drug consumption behaviors with
regard to time of day and week. Furthermore, by studying the accounts followed
by the users of drug related posts, we hope to discover common interests shared
by drug users.
