Behavioral Tracing of Twitter Accounts

“Trolls” individuals who engage in malicious behavior are a common occurrence within online communities. Yet simply banning accounts associated with trolls is often ineffective as individuals may register new accounts under pseudonyms and resume their activity. In this paper, we demonstrate how this can be addressed through a behavioral trace. Specifically, we show that by analyzing the posts of an account, we can derive a semantic signature unique to the account’s owner. By comparing the signatures of two accounts, we can determine whether they belong to the same user. We validate our techniques on a dataset of Twitter users, and explore different properties of our methods.