"Authorship Analysis on Dark Marketplace Forums", Spitters et al 2015:
Anonymity networks like Tor harbor many underground markets and discussion forums dedicated to the trade of illegal goods and services. As they are gaining in popularity, the analysis of their content and users is becoming increasingly urgent for many different parties, ranging from law enforcement and security agencies to financial institutions. A major issue in cyber forensics is that anonymization techniques like Tor's onion routing have made it very difficult to trace the identities of suspects. In this paper we propose classification set-ups for two tasks related to user identification, namely alias classification and authorship attribution. We apply our techniques to data from a Tor discussion forum mainly dedicated to drug trafficking, and show that for both tasks we achieve high accuracy using a combination of character-level n-grams, stylometric features and timestamp features of the user posts.
Ah, stylometric analysis. I've had an idea for a long time for a service for vendors to beat stylometrics analysis, just haven't ever seen the interest. While we're on the subject, I may as well plug anonymouth, a tool to help anonymize what you write to prevent compromise by textual identification.