The thesis reconstructed and analysed transaction-level data of a particular darknet market. Moreover, the thesis reveals what kind of vendors are active on this darknet market, based on their characteristics. Finally, this research identified what the relative importance is of different vendor characteristics for vendor performance on darknet markets.

Background: A lot of scientists have tried to shed light on dark web markets. They did this by scraping these marketplaces over a period of time and describe what they were seeing. However, the methods used to measure these markets were never validated before. Research goal: This research will identify and validate the methods that are used in the literature to measure darknet marketplaces. Methods: To validate these methods, a novel dataset is used, namely the confiscated backend of a market. This dataset is cleaned and used to analyze the accuracy of these proxies on. Results: It is found that the number of transactions, revenue, and market share can be estimated with a high amount of explained variance. The predictions are precise enough to find prominent vendors on the market. The designed method of calculating the illegally obtained profits of a darknet vendor is easy to understand and could be used by law enforcement agencies. Finally, it is found that some vendors register to a market early as a strategy to ensure their business continuity.