  Nowadays, the exponentially growing of the Web renders the problem of
correlation among different topics of paramount importance. The proposed model
can be used to study the evolution of network depicted by different topics on
the web correlated by a dynamic "fluid" of tags among them. The fluid-dynamic
model depicted is completely evolutive, thus it is able to describe the dynamic
situation of a network at every instant of time. This overcomes the
difficulties encountered by many static models. The theory permits the
development of efficient numerical schemes also for very large networks. This
is possible since dynamic flow at junctions is modeled in a simple and
computationally convenient way (resorting to a linear programming problem). The
obtained model consists of a single conservation law and is on one side simple
enough to permit a complete understanding, on the other side reach enough to
detect the evolution of the dynamic network.
