@inproceedings{018fb106d82b4e4d863085c67c31dd17,
title = "Detecting illicit drugs on social media using Automated Social Media Intelligence Analysis (ASMIA)",
abstract = "While social media is a new and exciting technology, it has the potential to be misused by organized crime groups and individuals involved in the illicit drugs trade. In particular, social media provides a means to create new marketing and distribution opportunities to a global marketplace, often exploiting jurisdictional gaps between buyer and seller. The sheer volume of postings presents investigational barriers, but the platform is amenable to the partial automation of open source intelligence. This paper presents a new methodology for automating social media data, and presents two pilot studies into its use for detecting marketing and distribution of illicit drugs targeted at Australians. Key technical challenges are identified, and the policy implications of the ease of access to illicit drugs are discussed.",
keywords = "illicit drugs, open source intelligence, social media",
author = "Watters, {Paul A.} and Nigel Phair",
year = "2012",
doi = "10.1007/978-3-642-35362-8_7",
language = "English",
isbn = "9783642353611",
series = "Lecture Notes in Computer Science",
publisher = "Springer, Springer Nature",
number = "7672",
pages = "66--76",
editor = "Yang Xiang and Javier Lopez and Kuo, {C.-C. Jay} and Wanlei Zhou",
booktitle = "Cyberspace Safety and Security",
address = "United States",
note = "4th International Symposium on Cyberspace Safety and Security, CSS 2012 ; Conference date: 12-12-2012 Through 13-12-2012",
}