This article tackles the issue of the detection of the user's likes and dislikes in a negotiation with a virtual agent for helping the creation of a model of user's preferences. We introduce a linguistic model of user's likes and dislikes as they are expressed in a negotiation context. The identification of syntactic and semantic features enables the design of formal grammars embedded in a bottom-up and rule-based system. It deals with conversational context by considering simple and collaborative likes and dislikes within adjacency pairs. We present the annotation campaign we conduct by recruiting annotators on CrowdFlower and using a dedicated annotation platform. Finally, we measure agreement between our system and the human reference. The obtained scores show substantial agreement