  In this paper, we propose a method of ranking recently created Twitter
accounts according to their prospective popularity. Early detection of new
promising accounts is useful for trend prediction, viral marketing, user
recommendation, and so on. New accounts are, however, difficult to evaluate
because they have not established their reputations, and we cannot apply
existing link-based or other popularity-based account evaluation methods. Our
method first finds "early adopters", i.e., users who often find new good
information sources earlier than others. Our method then regards new accounts
followed by good early adopters as promising, even if they do not have many
followers now. In order to find good early adopters, we estimate the frequency
of link propagation from each account, i.e., how many times the follow links
from the account have been copied by its followers. If its followers have
copied many of its follow links in the past, the account must be an early
adopter, who find good information sources earlier than its followers. We
develop a method of inferring which links are created by copying which links.
One advantage of our method is that our method only uses information that can
be easily obtained only by crawling neighbors of the target accounts in the
current Twitter graph. We evaluated our method by an experiment on Twitter
data. We chose then-new accounts from an old snapshot of Twitter, compute their
ranking by our method, and compare it with the number of followers the accounts
currently have. The result shows that our method produces better rankings than
various baseline methods, especially for new accounts that have only a few
followers.
