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.

翻译：在线市场是合法和非法电子商务的主要引擎,但买方-卖方网络背后的总体性质却不甚清楚。我们分析了2010年至2021年期间在线市场上发生的包含245M交易(16B美元)的两套数据集。数据涵盖28个黑暗的网络市场,即主要货币为比特币的无管制市场,以及一个受监管的电子商务平台的144个产品市场。我们展示了网上市场的交易如何显示出惊人的相似的总体行为模式,尽管语言、寿命期、现有产品、监管、监督和技术存在巨大差异。我们发现(一)交易额、(二)交易次数、(三)活动间交易次数、(四)第一次交易与最后一次交易之间的时间等显著的规律性。我们随后展示了买方行为如何受到过去互动记忆的影响,并利用这些观察来提出能够复制数据主要典型事实的网络形成模式。我们的调查结果对了解网上市场以及市场竞争的市场力量产生了影响。