  This master's thesis work has the objective of performing an analysis of the
methods for detecting communities in networks. As an initial part, I study of
the main features of graph theory and communities, as well as common measures
in this problem. Subsequently, I was performed a review of the main methods of
detecting communities, developing a classification, taking into account its
characteristics and computational complexity for the detection of strengths and
weaknesses in the methods, as well as later works. Then, study the problem of
classification of a clustering method, this in order to evaluate the quality of
the communities detected by analyzing different measures. Finally conclusions
are elaborated and possible lines of work that can be derived.
