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Hussam Hamdan, PhD en informatique, a travaillé sur le projet AgoraWeb (2012-2015) qui consistait à développer des méthodes numériques pour rechercher efficacement sur le Web un ensemble pertinent d’informations et de commentaires liés à la parution d’ouvrage et d’analyser automatiquement des passages de texte faisant référence à tout ouvrage. Les résultats présentés dans cet article font suite au travail d'annotation réalisé sur un corpus de comptes-rendus issus des plateformes Revues.org et Hypothèses : http://lab.hypotheses.org/1384 So far different studies have tackled the sentiment analysis in several domains such as restaurant and movie reviews. But, this problem has not been studied in scholarly book reviews which is different in terms of review style and size. In this paper, we propose to combine different features in order to be presented to a supervised classifiers which extract the opinion target expressions and detect their polarities in scholarly book reviews. We construct a labeled corpus for training and evaluating our methods in French book reviews. We also evaluate them on English restaurant reviews in order to measure their robustness across the domains and languages. The evaluation shows that our methods are enough robust for English restaurant reviews and French book reviews.URL: http://arxiv.org/abs/1603.01595