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Drug use by people is on the rise and is of great interest to public healthagencies and law enforcement agencies. As found by the National Survey on DrugUse and Health, 20 million Americans aged 12 years or older consumed illicitdrugs in the past few 30 days. Given their ubiquity in everyday life, drugabuse related studies have received much and constant attention. However, mostof the existing studies rely on surveys. Surveys present a fair number ofproblems because of their nature. Surveys on sensitive topics such as illicitdrug use may not be answered truthfully by the people taking them. Selecting arepresentative sample to survey is another major challenge. In this paper, weexplore the possibility of using big data from social media in order tounderstand illicit drug use behaviors. Instagram posts are collected using drugrelated terms by analyzing the hashtags supplied with each post. A large anddynamic dictionary of frequent illicit drug related slang is used to find theseposts. These posts are studied to find common drug consumption behaviors withregard to time of day and week. Furthermore, by studying the accounts followedby the users of drug related posts, we hope to discover common interests sharedby drug users.

Understanding Illicit Drug Use Behaviors by Mining Social Media