  This article presents two studies conducted with an affective dialogue system
in which text-based system-user communication was used to model, generate, and
present different affective and social interaction scenarios. We specifically
investigated the influence of interaction context and roles assigned to the
system and the participants, as well as the impact of pre-structured social
interaction patterns that were modelled to mimic aspects of 'social exclusion'
scenarios. The results of the first study demonstrate that both the social
context of the interaction and the roles assigned to the system influence the
system evaluation, interaction patterns, textual expressions of affective
states, as well as emotional self-reports. The results observed for the second
study show the system's ability to partially exclude a participant from a
triadic conversation without triggering significantly different affective
reactions or a more negative system evaluation. The experimental evidence
provides insights on the perception, modelling and generation of affective and
social cues in artificial systems that can be realized in different modalities,
including the text modality, thus delivering valuable input for applying
affective dialogue systems as tools for studying affect and social aspects in
online communication.
