  Suppose you find the same username on different online services, what is the
probability that these usernames refer to the same physical person? This work
addresses what appears to be a fairly simple question, which has many
implications for anonymity and privacy on the Internet. One possible way of
estimating this probability would be to look at the public information
associated to the two accounts and try to match them. However, for most
services, these information are chosen by the users themselves and are often
very heterogeneous, possibly false and difficult to collect. Furthermore,
several websites do not disclose any additional public information about users
apart from their usernames (e.g., discus- sion forums or Blog comments),
nonetheless, they might contain sensitive information about users. This paper
explores the possibility of linking users profiles only by looking at their
usernames. The intuition is that the probability that two usernames refer to
the same physical person strongly depends on the "entropy" of the username
string itself. Our experiments, based on crawls of real web services, show that
a significant portion of the users' profiles can be linked using their
usernames. To the best of our knowledge, this is the first time that usernames
are considered as a source of information when profiling users on the Internet.
