Affective Computing aims at improving the naturalness of human-computer interactions by integrating the socio-emotional component in the interaction. The use of embodied conversational agents (ECAs) – virtual characters interacting with humans – is a key answer to this issue. On the one hand, the ECA has to take into account the human emotional behaviours and social attitudes. On the other hand, the ECA has to display socio-emotional behaviours with relevance. In this paper, we provide an overview of computational methods used for user’s socio-emotional behaviour analysis and of human-agent interaction strategies by questioning the ambivalent status of surprise. We focus on the computational models and on the methods we use to detect user’s emotion through language and speech processing and present a study investigating the role of surprise in the ECA’s answer.