  In this work we focus on identifying key players in dark net cryptomarkets
that facilitate online trade of illegal goods. Law enforcement aims to disrupt
criminal activity conducted through these markets by targeting key players
vital to the market's existence and success. We particularly focus on detecting
successful vendors responsible for the majority of illegal trade. Our
methodology aims to uncover whether the task of key player identification
should center around plainly measuring user and forum activity, or that it
requires leveraging specific patterns of user communication. We focus on a
large-scale dataset from the Evolution cryptomarket, which we model as an
evolving communication network. Results indicate that user and forum activity,
measured through topic engagement, is best able to identify successful vendors.
Interestingly, considering users with higher betweenness centrality in the
communication network further improves performance, also identifying successful
vendors with moderate activity on the forum. But more importantly, analyzing
the forum data over time, we find evidence that attaining a high betweenness
score comes before vendor success. This suggests that the proposed
network-driven approach of modelling user communication might prove useful as
an early warning signal for key player identification.
