GAM Models M1 and M2.

The emergence of social order on darknet markets presents social scientists with a unique puzzle. Because these markets operate outside of conventional regulatory frameworks, there is a lack of legitimate oversight to monitor transactions and protect users from opportunistic behaviour. While existing literature often examines the role of reputation in increasing sales, little attention has been paid to mechanisms that mitigate fraud. This study fills this gap by examining one of the largest known darknet platforms, Alphabay, which was operational from December 2014 to July 2017. Using two Generalised Additive Models (GAMs), results show that costly signals, such as a positive reputation, sellers’ seniority and escrow services, are inversely associated with fraudulent activity on darknet markets. Conversely, cheap signals, such as long product descriptions characterised by complex vocabulary and a positive tone, correlate positively with opportunistic behaviour. The study provides empirical support for signalling theory, by showing that costly signals are more difficult to fake or manipulate and can reduce fraud. Conversely, the study also demonstrates empirically that cheap signals, while potentially effective in initially generating trust among buyers, are associated with an increase in fraud and opportunistic behaviour.