  A natural way to resolve different points of view and form opinions is
through exchanging arguments and knowledge. Facing the vast amount of available
information on the internet, people tend to focus on information consistent
with their beliefs. Especially when the issue is controversial, information is
often selected that does not challenge one's beliefs. To support a fair and
unbiased opinion-building process, we propose a chatbot system that engages in
a deliberative dialogue with a human. In contrast to persuasive systems, the
envisioned chatbot aims to provide a diverse and representative overview -
embedded in a conversation with the user. To account for a reflective and
unbiased exploration of the topic, we enable the system to intervene if the
user is too focused on their pre-existing opinion. Therefore we propose a model
to estimate the users' reflective engagement (RUE), defined as their critical
thinking and open-mindedness. We report on a user study with 58 participants to
test our model and the effect of the intervention mechanism, discuss the
implications of the results, and present perspectives for future work. The
results show a significant effect on both user reflection and total user focus,
proving our proposed approach's validity.
