Abstract
In this paper, we present the experimental design for the evaluation of the impact of social signal application on a user's decision making in the area of telecommunications. The aim of the design is to show that user's social signals are applicable feedbacks in conversational recommender systems. We use user satisfaction (with the system and content) evaluation criteria. During social interaction humans express social signals which provide quick feedbacks required by conversational recommender system. The experimental scenario is hands driven video-on-demand service with a conversational recommender system where the user selects among videos on screen. We limited our experimental scenario to the social signal of hesitation only. User is hesitating, when is faced with a variety of choices to make decisions (he is uncertain). The system adjusts the list of items to be recommended according to the extracted social signal {hesitation, no hesitation}.