Conversational agents are increasingly present in our daily lives thanks to advances in natural language processing and artificial intelligence and are attracting growing interest. However, their ability to understand human communication in all its complexity remains a major challenge. This PhD project aims to model linguistic variation to develop agents capable of socially adaptive interactions, taking into account the socio-demographic profile and emotional state of their interlocutors. It also focuses on evaluating linguistic cues at different levels, leveraging both spoken and written language varieties, and assessing the generalization capacity of models trained on multilingual and multi-situational data, with the goal of improving interaction modeling with conversational agents.