“Network Structure and Trust Formation in Cryptomarkets Based on Reputation”, 2024-06-27 (; similar):
This chapter examines the network structure of a cryptomarket in order to identify the market-level metrics that predict vendor selection. These findings provide more insight into how trust among buyers and vendors determines the structure of a cryptomarket. In particular, this chapter seeks to test the generalizability of 2017’s initial study [cf. 2018] to determine if preferential attachment under trust dynamics plays a role in the topology of a cryptomarket. Furthermore, this study offers insight into the predictors and the development trajectory of vendor trustworthiness.
These findings indicate that Abraxas, the cryptomarket under examination, possessed a markedly diffuse transactional network. Moreover, Abraxas buyers tended to purchase from a small number of vendors over time, which led to the formation of a large group of sparsely connected users with very few isolated buyer-seller cliques. The Abraxas transactional network can thus be viewed as a set of transactional islands as opposed to a large, densely connected conglomeration of vendors and buyers. It is also important to note that these transactional communities within the network were country & product-specific, meaning that a specific product type was shipped to a single country.
Regression analyses for vendor success, popularity and affluence demonstrated that the cumulative reputation score of vendors was the predominant predictor for trust across all 3 proxy variables. Additionally, cumulative risk was the second statistically-significant predictor across all 3 models. This indicates that a vendor’s willingness to incur the risks associated with overseas shipping yields greater economic opportunities and with it a reputation for trustworthy conduct.
Finally, the trajectory models demonstrate that a small number of vendors become highly successful, popular and affluent in a relatively short period of time. Moreover, vendors that possess a specific ranking within the market are likely to conserve this ranking throughout the market’s operation: Low-achieving vendors tend to remain low-achieving, while high-achieving vendors become increasingly successful, popular and affluent.
These findings are key for the development of effective law enforcement interventions against cryptomarkets. In sum, the targeted disruption of trust and reputational dynamics within cryptomarkets may yield greater deterrent returns than a large-scale market takedown.