# Collective Dynamics of Dark Web Marketplaces

arXiv: https://arxiv.org/abs/1911.09536 · HTML: https://mlsanity.com/paper/1911.09536/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2019.

## Built on by (most cited first, 4 of 4)

- [SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis](https://mlsanity.com/paper/2104.00764/) (2021)
- [NBC-Softmax : Darkweb Author fingerprinting and migration tracking](https://mlsanity.com/paper/2212.08184/) (2022)
- [URM4DMU: an user represention model for darknet markets users](https://mlsanity.com/paper/2303.10674/) (2023)
- ["Can We Detect Substance Use Disorder?": Knowledge and Time Aware Classification on Social Media from Darkweb](https://mlsanity.com/paper/2304.10512/) (2023)

## Abstract (arXiv)

Dark markets are commercial websites that use Bitcoin to sell or broker transactions involving drugs, weapons, and other illicit goods. Being illegal, they do not offer any user protection, and several police raids and scams have caused large losses to both customers and vendors over the past years. However, this uncertainty has not prevented a steady growth of the dark market phenomenon and a proliferation of new markets. The origin of this resilience have remained unclear so far, also due to the difficulty of identifying relevant Bitcoin transaction data. Here, we investigate how the dark market ecosystem re-organises following the disappearance of a market, due to factors including raids and scams. To do so, we analyse 24 episodes of unexpected market closure through a novel datasets of 133 million Bitcoin transactions involving 31 dark markets and their users, totalling 4 billion USD. We show that coordinated user migration from the closed market to coexisting markets guarantees overall systemic resilience beyond the intrinsic fragility of individual markets. The migration is swift, efficient and common to all market closures. We find that migrants are on average more active users in comparison to non-migrants and move preferentially towards the coexisting market with the highest trading volume. Our findings shed light on the resilience of the dark market ecosystem and we anticipate that they may inform future research on the self-organisation of emerging online markets.