Online social network (OSN) accounts are often more user-centric than other types of online accounts (e.g., email accounts) because they present a number of demographic attributes such as age, gender, location, and occupation. While these attributes allow for more meaningful online interactions, they can also be used by malicious parties to craft various types of abuse. To understand the effects of demographic attributes on attacker behavior in stolen social accounts, we devised a method to instrument and monitor such accounts. We then created, instrumented, and deployed more than 1000 Facebook accounts, and exposed them to criminals. Our results confirm that victim demographic traits indeed influence the way cybercriminals abuse their accounts. For example, we find that cybercriminals that access teen accounts write messages and posts more than the ones accessing adult accounts, and attackers that compromise male accounts perform disruptive activities such as changing some of their profile information more than the ones that access female accounts. This knowledge could potentially help online services develop new models to characterize benign and malicious activity across various demographic attributes, and thus automatically classify future activity.