  Complex networks often exhibit co-evolutionary dynamics, meaning that the
network topology and the state of nodes or links are coupled, affecting each
other in overlapping time scales. We focus on the co-evolutionary dynamics of
online social networks, and on Twitter in particular. Monitoring the activity
of thousands of Twitter users in real-time, and tracking their followers and
tweets/retweets, we propose a method to infer new retweet-driven follower
relations. The formation of such relations is much more likely than the
exogenous creation of new followers in the absence of any retweets. We identify
the most significant factors (reciprocity and the number of retweets that a
potential new follower receives) and propose a simple probabilistic model of
this effect. We also discuss the implications of such co-evolutionary dynamics
on the topology and function of a social network.
