  The ever-increasing amount of information flowing through Social Media forces
the members of these networks to compete for attention and influence by relying
on other people to spread their message. A large study of information
propagation within Twitter reveals that the majority of users act as passive
information consumers and do not forward the content to the network. Therefore,
in order for individuals to become influential they must not only obtain
attention and thus be popular, but also overcome user passivity. We propose an
algorithm that determines the influence and passivity of users based on their
information forwarding activity. An evaluation performed with a 2.5 million
user dataset shows that our influence measure is a good predictor of URL
clicks, outperforming several other measures that do not explicitly take user
passivity into account. We also explicitly demonstrate that high popularity
does not necessarily imply high influence and vice-versa.
