Journal article
Web scraping of ecstasy user reports as a novel tool for detecting drug market trends
Forensic Science International: Digital Investigation, Vol.37, Article 301172
2021
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.
Details
- Title
- Web scraping of ecstasy user reports as a novel tool for detecting drug market trends
- Authors/Creators
- J. Maybir (Author/Creator)B. Chapman (Author/Creator)
- Publication Details
- Forensic Science International: Digital Investigation, Vol.37, Article 301172
- Publisher
- Elsevier
- Identifiers
- 991005544213207891
- Copyright
- © 2021 Elsevier Ltd
- Murdoch Affiliation
- School of Medical, Molecular and Forensic Sciences
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
480 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Citation topics
- 1 Clinical & Life Sciences
- 1.100 Substance Abuse
- 1.100.809 Psychoactive Substances
- Web Of Science research areas
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- ESI research areas
- Computer Science