Mobile application developers can extract useful information from reviews that people post on mobile distribution platforms to improve the services they provide. The classification of such reviews can be automatized through Machine Learning techniques implementing a task of Natural Language Processing: Text Classification. Several challenges are faced in this thesis work, developed in cooperation with Ariston S.p.A, an Italian corporation that produces heating systems and related products. They concern data distribution and taxonomy of classes, both put at the disposal and established by the company itself. In particular, the adopted taxonomy is structured in a two-levels manner: five macro-categories branching out into several other sub-categories and reaching thus a total number of 24 classes.