User menu

Accès à distance ? S'identifier sur le proxy UCLouvain

Drug name recognition in the cryptomarket forum of Silk Road 2

Primary tabs

Werner, Romane [UCL] François, Thomas [UCL] Bitzer, Sonja [UCL]

Drug forums and online chat rooms constitute a relevant source of information for drug use, whose content can serve as reliable sources of information for national agencies with a high number of discussions taking place on various topics. We aimed at investigating whether forum posts could provide useful information as regards to both the early appearance and the monitoring of drug names. A Drug Name Recognition system was used to extract drug terms from the cryptomarket forum of Silk Road 2 thanks to a Conditional Random Fields model. Results of our analysis showed that our model enabled us to discover the presence of 232 new drug names compared to the presence of 106 traditional drug names, which reflect the importance of internet traces as being robust and exploitable with respect to crime phenomena.

Document type Communication à un colloque (Conference Paper) – Poster
Publication date 2023
Language Anglais
Conference "CLiC-it 2023", Venice (du 30/11/2023 au 02/12/2023)
Peer reviewed yes
Affiliations UCL - SSH/SPLE - Institut de sciences politiques Louvain-Europe
UCL - SSH/ILC - Institut Langage et Communication
UCL - SSH/JURI - Institut pour la recherche interdisciplinaire en sciences juridiques
Keywords CRF ; NLP ; DNR ; cryptomarket
Links
Bibliographic reference Werner, Romane ; François, Thomas ; Bitzer, Sonja. Drug name recognition in the cryptomarket forum of Silk Road 2.CLiC-it 2023 (Venice, du 30/11/2023 au 02/12/2023).
Permanent URL http://hdl.handle.net/2078.1/285694