No abstract

Today, the need to automatically process opinions is strongly felt. It is in this context that we situate this work whose objective is to contribute to the achievement of opinions analysis system, enabling a binary classification on a set of textual data. For this, we studied and evaluated several methods, Support Vector Machines (SVM) and Naïve Bayes (NB), on a corpus composed of 500 journals films. These models have not been satisfactory. To improve the results we have introduced a pre-treatment phase or standardization corpus before classification; this phase has improved the quality of the classification.