- Title
- Detecting illicit drugs on social media using Automated Social Media Intelligence Analysis (ASMIA)
- Creator
- Watters, Paul; Phair, Nigel
- Date
- 2012
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/31923
- Identifier
- vital:4880
- Identifier
-
https://doi.org/10.1007/978-3-642-35362-8_7
- Identifier
- ISBN:03029743 (ISSN); 9783642353611 (ISBN)
- 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. © 2012 Springer-Verlag.
- Publisher
- Melbourne, VIC Springer Berlin Heidelberg
- Relation
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7672 LNCS, p. 66-76
- Rights
- Copyright 2012 Springer-Verlag
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Global marketplaces; Illicit drug; Intelligence analysis; Open source intelligence; Partial automation; Pilot studies; Policy implications; Social media; Technical challenges; Commerce; Computers; Marketing; Public policy; Drug products
- Full Text
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