An unsupervised machine learning approach for the detection and characterization of illicit drug-dealing comments and interactions on Instagram.

ABSTRACT: Background: Growing use of social media has led to the emergence of virtual controlled substance and illicit drug marketplaces, prompting calls for action by government and law enforcement. Previous studies have analyzed Instagram drug selling via posts. However, comments made by users involving potential drug selling have not been analyzed. In this study, we use unsupervised machine learning to detect and classify prescription and illicit drug-related buying and selling interactions on Instagram. Methods: We used over 1,000 drug-related hashtags on Instagram to collect a total of 43,607 Instagram comments between February 1st, 2019 and May 31st, 2019 using data mining approaches in the Python programming language. We then used an unsupervised machine learning approach, the B

SUBMITTER: Shah N 

PROVIDER: S-EPMC9675406 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature