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Detecting Illicit Drugs on Social Media Using Automated Social Media Intelligence Analysis (ASMIA)

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Cyberspace Safety and Security (CSS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7672))

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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.

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Author information

Authors and Affiliations

  1. Internet Commerce Security Laboratory (ICSL), University of Ballarat, Ballarat, Australia

    Paul A. Watters

  2. Centre for Internet Safety, University of Canberra, Canberra, Australia

    Nigel Phair

Authors
  1. Paul A. Watters
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  2. Nigel Phair
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Editor information

Editors and Affiliations

  1. School of Information Technology, Deakin University, 221 Burwood Highway, 3125, Burwood, VIC, Australia

    Yang Xiang  & Wanlei Zhou  & 

  2. Computer Science Department, ETSI Informatica, University of Malaga, Campus de Teatinos, 29170, Malaga, Spain

    Javier Lopez

  3. Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Ave., 90089-2564, Los Angeles, CA, USA

    C.-C. Jay Kuo

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© 2012 Springer-Verlag Berlin Heidelberg

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Watters, P.A., Phair, N. (2012). Detecting Illicit Drugs on Social Media Using Automated Social Media Intelligence Analysis (ASMIA). In: Xiang, Y., Lopez, J., Kuo, CC.J., Zhou, W. (eds) Cyberspace Safety and Security. CSS 2012. Lecture Notes in Computer Science, vol 7672. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35362-8_7

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  • DOI: https://doi.org/10.1007/978-3-642-35362-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35361-1

  • Online ISBN: 978-3-642-35362-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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