User names of illegal drug vendors on a darknet cryptomarket

Abstract

The illegal drug trade has recently found a new route: darknet cryptomarkets. On these Ebay-like marketplaces, located in an anonymous network, drug sellers and buyers from all over the world make deals without meeting each other in person. Drug vendors are known by their user names, and those names could have a huge financial significance for their owners. This study examines the characteristics of those vendor user names and contrasts them to both other types of user names as well as to real-life commercial names. The data for the study were collected from AlphaBay, which was the largest cryptomarket in early 2017. Many vendors share information of themselves through their user names, referring to their products, home country and whether they work alone or in a group. Names are also used to create various images of vendor's business. Some vendors try to create an image of a normal, legal business by using company and brand name vocabulary or by plagiarising famous real-life brand names. Other vendors, however, appear to even highlight their criminality, referring to illegal activities or well-known 46 LASSE HÄMÄLÄINEN real-life or fictional drug criminals. Vendor names also include references to the desired effects of drugs and the high quality of products and service. One-third of names are not connected to drugs in any visible way. Overall, vendor names more closely resemble other user names, but they clearly have also been influenced by commercial names.

Drug traders on a local dark web marketplace

“…Compared to a previous study about usernames in the now defunct cryptomarket AlphaBay [25], the percentage of drugrelated names was relatively low. Usernames that were not related to drugs included a wide range of different themes -for example personal names, place names, fictional characters, and made-up words.…”

“…Some users may therefore want to express that they are native, ethnic Finns. This stands in contrast to international sites like AlphaBay, where nationality could be connected more strongly to locality, and thus also the availability of drugs in an area, instead of ethnicity-related trust [25].…”

“…After quantitative analysis, a qualitative analysis was conducted. The analysis was based on functional-semantic analysis method, originally created for the study of commercial names by Sjöblom [36] and later adapted to username studies by Hämäläinen [25,26]. In this method, usernames are first divided into separate name parts according to the functions of those parts.…”

Nimet verkossa (tulossa)

“…Neljännessä artikkelissa (Hämäläinen 2018) jatkan Aapelin Minigolfin radannimien tutkimista muistettavuuden näkökulmasta. Tutkimuskysymykseni on siis, millaiset ni met ovat helppoja tai vaikeita muistaa.…”

Information Protection in Dark Web Drug Markets Research

“…In this paper, we look into how research conducted on Dark Web cryptomarkets and drug trading imageboards, particularly machine-based research, should protect data and the communities being researched while carrying our needed research around, for example, drug policy (e.g., [6;7]), understanding anonymity technologies (e.g., [3;4]), disnormative information practices (e.g., [8;9;10]), or user name selection (e.g., [11]).…”