  This work analyzes the problem of community structure in real-world networks
based on the synchronization of nonidentical coupled chaotic R\"{o}ssler
oscillators each one characterized by a defined natural frequency, and coupled
according to a predefined network topology. The interaction scheme contemplates
an uniformly increasing coupling force to simulate a society in which the
association between the agents grows in time. To enhance the stability of the
correlated states that could emerge from the synchronization process, we
propose a parameterless mechanism that adapts the characteristic frequencies of
coupled oscillators according to a dynamic connectivity matrix deduced from
correlated data. We show that the characteristic frequency vector that results
from the adaptation mechanism reveals the underlying community structure
present in the network.
