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Consumers are used to consulting posted reviews on the Internet before buyinga product. But it's difficult to know the global opinion considering theimportant number of those reviews. Sentiment analysis afford detecting polarity(positive, negative, neutral) in a expressed opinion and therefore classifyingthose reviews. Our purpose is to determine the influence of emotions on thepolarity of books reviews. We define "bag-of-words" representation models ofreviews which use a lexicon containing emotional (anticipation, sadness, fear,anger, joy, surprise, trust, disgust) and sentimental (positive, negative)words. This lexicon afford measuring felt emotions types by readers. Theimplemented supervised learning used is a Random Forest type. The applicationconcerns Amazon platform's reviews. Mots-cl{\'e}s : Analyse de sentiments,Analyse d'{\'e}motions (texte), Classification de polarit{\'e} de sentiments

Emotion and Sentiment Lexicon Impact on Sentiment Analysis Applied to Book Reviews