The rise in illicit drug trafficking on darknet markets (DNMs) was boosted by those restrictions imposed due to the COVID-19 pandemic. This study aims to put this trend into context by exploring the characteristics of vendors’ services and reputations and understand how products are advertised and what customers tend to value. Qualitative content analysis was conducted on a sample (n = 100) randomly selected from 6,357 product descriptions and a sample (n = 500) randomly selected from 34,619 reviews. Both samples are from products found in the drug category of the darknet market Dark0de Reborn. On the supply side, vendors tended to provide basic information on the drugs, a mention of their high quality, the speed and stealth of delivery, their availability for responding to messages, the effects of the drugs, and sometimes even instructions for use. Regarding the demand side, customers usually praised the quality of the product, mentioned the speed and stealth-secure packaging of delivery as essentials, and expressed only a small number of issues. These results support the applicability of Norbert Elias’ social figuration theory in which the interdependencies of the actors are fueled by trust. This theoretical frame sheds light on the social value of the community of DNMs. Furthermore, the findings formulate a robust hypothesis for future research about the previously undervalued role of delivery providers.
BahamazavaK.NandaR. (2022). The shift of DarkNet illegal drug trade preferences in cryptocurrency: The question of traceability and deterrence. Forensic Science International: Digital Investigation, 40, Article 301377. https://doi.org/10.1016/j.fsidi.2022.301377
3.
BancroftA.ReidP. S. (2016). Concepts of illicit drug quality among darknet market users: Purity, embodied experience, craft and chemical knowledge. International Journal of Drug Policy, 35, 42–49. https://doi.org/10.1016/j.drugpo.2015.11.008
4.
BancroftA.ReidP. S. (2017). Challenging the techno-politics of anonymity: The case of cryptomarket users. Information. Communication & Society, 20(4), 497–512. https://doi.org/10.1080/1369118x.2016.1187643
5.
BroséusJ.RhumorbarbeD.MireaultC.OuelletteV.CrispinoF.Décary-HétuD. (2016). Studying illicit drug trafficking on Darknet markets: Structure and organisation from a Canadian perspective. Forensic Science International, 264, 7–14. https://doi.org/10.1016/j.forsciint.2016.02.045
DolliverD. S.KenneyJ. L. (2016). Characteristics of drug vendors on the tor network: A cryptomarket comparison. Victims & Offenders, 11(4), 600–620. https://doi.org/10.1080/15564886.2016.1173158
10.
EliasN. (2000). The civilizing process: Sociogenetic and psychogenetic investigations (JephcottE., Trans., Revised ed.). Blackwell.
11.
EspinosaR. (2019). Scamming and the reputation of drug dealers on darknet markets. International Journal of Industrial Organization, 67, Article 102523. https://doi.org/10.1016/j.ijindorg.2019.102523
12.
European Monitoring Centre for Drugs and Drug Addiction. & European Police Office. (2020). EU drug markets: Impact of COVID 19. Publications Office. https://doi.org/10.2810/19284
GambettaD. (2009). Codes of the underworld: How criminals communicate. Princeton University Press.
15.
GoldschlagD. M.ReedM. G.SyversonP. F. (1996). Hiding routing information. In AndersonR. (Eds.), International workshop on information hiding (pp. 137–150). Springer.
16.
HoltT. J.SmirnovaO.HutchingsA. (2016). Examining signals of trust in criminal markets online. Journal of Cybersecurity, 2(2), 137–145. https://doi.org/10.1093/cybsec/tyw007
JardineE. (2015, September). The dark web dilemma: Tor, anonymity and online policing. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2667711
20.
JardineE. (2018). The trouble with (supply-side) counts: The potential and limitations of counting sites, vendors or products as a metric for threat trends on the dark web. Intelligence and National Security, 34(1), 95–111. https://doi.org/10.1080/02684527.2018.1528752
21.
KamphausenG.WerseB. (2019). Digital figurations in the online trade of illicit drugs: A qualitative content analysis of darknet forums. International Journal of Drug Policy, 73, 281–287. https://doi.org/10.1016/j.drugpo.2019.04.011
22.
KuckartzU. (2019). Qualitative text analysis: A systematic approach. In KaiserG.PresmegN. (Eds.), Compendium for early career researchers in mathematics education—ICME-13 monographs (pp. 181–197). Springer. https://doi.org/10.1007/978-3-030-15636-7_8
23.
LaferrièreD.Décary-HétuD. (2023). Examining the u ncharted d ark w eb: Trust s ignalling on s ingle v endor s hops. Deviant Behavior, 44(1), 37–56. https://doi.org/10.1080/01639625.2021.2011479
24.
Lorenzo-DusN.Di CristofaroM. (2018). ‘I know this whole market is based on the trust you put in me and I don’t take that lightly’: Trust, community and discourse in crypto-drug markets. Discourse & Communication, 12(6), 608–626. https://doi.org/10.1177/1750481318771429
25.
MartinJ. (2014). Drugs on the dark net: How cryptomarkets are transforming the global trade in illicit drugs. Palgrave Pivot.
26.
MassonK.BancroftA. (2018). ‘Nice people doing shady things’: Drugs and the morality of exchange in the darknet cryptomarkets. International Journal of Drug Policy, 58, 78–84. https://doi.org/10.1016/j.drugpo.2018.05.008
NorbutasL.RuiterS.CortenR. (2020). Reputation transferability across contexts: Maintaining cooperation among anonymous cryptomarket actors when moving between markets. International Journal of Drug Policy, 76, Article 102635. https://doi.org/10.1016/j.drugpo.2019.102635
29.
PartiK.SzigetiA. (2021). The future of interdisciplinary research in the digital era: Obstacles and perspectives of collaboration in social and data sciences—an empirical study. Cogent Social Sciences, 7(1), Article 1970880. https://doi.org/10.1080/23311886.2021.1970880
30.
PergolizziJ. V.Jr.LeQuangJ. A.TaylorR.RaffaR. B.Jr., (2017). The “Darknet”: The new street for street drugs. Journal of Clinical Pharmacy and Therapeutics, 42(6), 790–792. https://doi.org/10.1111/jcpt.12628
31.
PrzepiorkaW.NorbutasL.CortenR. (2017). Order without law: Reputation promotes cooperation in a cryptomarket for illegal drugs. European Sociological Review, 33(6), 752–764. https://doi.org/10.1093/esr/jcx072
TufekciZ. (2014, June1–4). Big questions for social media big data: Representativeness, validity and other methodological pitfalls [Conference session]. ICWSM ‘14: 8th International AAAI Conference on Weblogs and Social Media, 2014, Cornell University. https://arxiv.org/pdf/1403.7400.pdf
36.
“World Drug Report.” (2020). Sales No. E.20.XI.6. United Nations.
37.
“World Drug Report.” (2021). Sales No. E.21.XI.8. United Nations.
