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Web scraping of ecstasy user reports as a novel tool for detecting drug market trends

Maybir, J. and Chapman, B.ORCID: 0000-0001-7518-6645 (2021) Web scraping of ecstasy user reports as a novel tool for detecting drug market trends. Forensic Science International: Digital Investigation, 37 . Art. 301172.

Link to Published Version: https://doi.org/10.1016/j.fsidi.2021.301172
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Abstract

Open-source intelligence (OSINT) is a technique involving the use of publicly available information for the purpose of addressing a specific intelligence issue. Open-source, user-reported data on ecstasy pills was extracted from a clear-web site known as Pill Reports (available at www.pillreports.net) and analysed to establish whether drug intelligence could be derived to assist law enforcement and policymakers in taking effective action against the illicit ecstasy market. A comprehensive database of 4358 ecstasy pills reported by users in Australia and New Zealand between September 2005 and April 2020 was established. Using this database, intelligence was gathered under two categories: general summary data and geographic movement trends. General summary data included pill characteristics (i.e., logo, colour and shape variations), regional distribution and temporal usage trends. Geographic movement data was used to ascertain whether a common sequence of flow (i.e., trafficking patterns) could be identified both (i) across state lines and (ii) east to west across Australia. Open-source investigation of online ecstasy report data proved to be most effective for obtaining general summary data which was concordant with other more costly and onerous population-wide approaches like wastewater analyses and population surveys. There was some evidence to suggest where MDMA is entering Australian borders, and an east-to-west onshore distribution pathway is suggested, taking approximately one year to run its course. This OSINT technique illustrates a novel strategic approach that can be used to monitor drug trends in real-time.

Item Type: Journal Article
Murdoch Affiliation(s): Medical, Molecular and Forensic Sciences
Publisher: Elsevier
Copyright: © 2021 Elsevier Ltd.
URI: http://researchrepository.murdoch.edu.au/id/eprint/61043
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