@article {644582,
	title = {Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation},
	journal = {Behavior \& Information Technology},
	year = {2019},
	abstract = {Joint narratives are often used in the context of reconciliation interventions for people in social conflict situations, which arise, for example, due to ethnic or religious differences. The interventions aim to encourage a change in attitudes of the participants towards each other. Typically, a human mediator is fundamental for achieving a successful intervention. In this work, we present an automated approach to support remote interactions between pairs of participants as they contribute to a shared story in their own language. A key component is an automated cognitive tutor that guides the participants through a controlled escalation/de-escalation process during the development of a joint narrative. We performed a controlled study comparing a trained human mediator to the automated mediator. The results demonstrate that an automated mediator, although simple at this stage, effectively supports interactions and helps to achieve positive outcomes comparable to those attained by the trained human mediator.},
	url = {https://www.tandfonline.com/doi/abs/10.1080/0144929X.2019.1637940?journalCode=tbit20},
	author = {Massimo Zancanaro and Oliviero Stock and Gianluca Schiavo and Alessandro Cappelletti and Sebastian Gehrmann and Daphna Canetti and Ohad Shaked and Shani Fachter and Rachel Yifat and Ravit Mimran and Patrice L. Weiss}
}
