Abstract : In the last years, emotions recognition tools have become more and more popular, aiming at detecting the emotions of human actors while performing different intelligent tasks by means of headsets and facial emotions detection tools. In addition to this kind of technology , when participants interact with each others by means of tex-tual exchanges, sentiment analysis techniques, from the natural language processing research area, are exploited to detect the polarity of the exchanged messages. Investigating how these two connected components interacts and can support each other towards a better emotions and sentiment detection is a relevant but unexplored research challenge. In this paper, we start from a dataset of debate interactions annotated with the emotions of the involved participants, captured by means of EEG headsets and a facial emotions recognition tool, and the argumentative structures of the debates, and we compare this information to the polarity of the proposed textual arguments, retrieved through a sentiment analysis algorithm. A pragma-semantic analysis of the obtained results is provided, along with a discussion of the potential future work.