In this paper, we described three systems developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic.
 We tried to show the interest of combining word-level and character-level features. In order to ease the choice of the type of character n-grams used as features we developed a baseline with a Logistic Regression classifier using character n-grams.
 It helped us to find an appropriate combination of features to produce the ensemble method whose results were submitted to this shared task.
  It appeared that adding tf-idf and class weighting made this baseline better than the ensemble method, showing maybe the interest of digging into character-level features.
  %In order to improve this method we think to combine classifiers with different set of features since it appeared that using the same set of features for each classifier may limit the complementarity between them.
