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This paper describes the methods we submitted to the DEFT 2015 Challenge (Text Mining Challenge). This eleventh edition concerned the analysis of opinions, sentiments and emotions expressed in French tweets. Three tasks have been proposed, we participated to task 1 which concerned the classification of tweets according to their polarities, to task 2.1 concerning the identification of the generic class of information expressed in the tweet, and finally to task 2.2 that concerned the identification of the specific class of opinion, sentiment or emotion. We proposed supervised methods based on support vector machines (SVM) using several types of attributes such as word n-grams, character n-grams, most common syntactic patterns, etc. Moreover, we constructed and used two French lexicons of sentiments and emotions.