Macroscopic properties of buyer-seller networks in online marketplaces

Online marketplaces are the main engines of legal and illegal e-commerce, yet the aggregate properties of buyer-seller networks behind them are poorly understood. We analyze two datasets containing 245M transactions (16B USD) that took place on online marketplaces between 2010 and 2021. The data cover 28 dark web marketplaces, i.e., unregulated markets whose main currency is Bitcoin, and 144 product markets of one regulated e-commerce platform. We show how transactions in online marketplaces exhibit strikingly similar patterns of aggregate behavior despite significant differences in language, lifetimes available products, regulation, oversight, and technology. We find remarkable regularities in the distributions of (i) transaction amounts, (ii) number of transactions, (iii) inter-event times, (iv) time between first and last transactions. We then show how buyer behavior is affected by the memory of past interactions, and draw on these observations to propose a model of network formation able to reproduce the main stylized facts of the data. Our findings have implications for understanding market power on online marketplaces as well as inter-marketplace competition.