  The lack of large-scale, continuously evolving empirical data usually limits
the study of networks to the analysis of snapshots in time. This approach has
been used for verification of network evolution mechanisms, such as
preferential attachment. However, these studies are mostly restricted to the
analysis of the first links established by a new node in the network and
typically ignore connections made after each node's initial introduction. Here,
we show that the subsequent actions of individuals, such as their second
network link, are not random and can be decoupled from the mechanism behind the
first network link. We show that this feature has strong influence on the
network topology. Moreover, snapshots in time can now provide information on
the mechanism used to establish the second connection. We interpret these
empirical results by introducing the propinquity model, in which we control and
vary the distance of the second link established by a new node, and find that
this can lead to networks with tunable density scaling, as found in real
networks. Our work shows that sociologically meaningful mechanisms are
influencing network evolution and provides indications of the importance of
measuring the distance between successive connections.
