  In the context of chit-chat dialogues it has been shown that endowing systems
with a persona profile is important to produce more coherent and meaningful
conversations. Still, the representation of such personas has thus far been
limited to a fact-based representation (e.g. "I have two cats."). We argue that
these representations remain superficial w.r.t. the complexity of human
personality. In this work, we propose to make a step forward and investigate
stance-based persona, trying to grasp more profound characteristics, such as
opinions, values, and beliefs to drive language generation. To this end, we
introduce a novel dataset allowing to explore different stance-based persona
representations and their impact on claim generation, showing that they are
able to grasp abstract and profound aspects of the author persona.
