Evaluating an automated mediator for joint narratives in a conflict situation

Massimo Zancanaro, Oliviero Stock, Gianluca Schiavo, Alessandro Cappelletti, Sebastian Gehrmann, Daphna Canetti, Ohad Shaked, Shani Fachter, Rachel Yifat, Ravit Mimran, Patrice L. Weiss

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)1022-1037
Number of pages16
JournalBehaviour and Information Technology
Issue number9
StatePublished - 1 Sep 2020

Bibliographical note

Publisher Copyright:
© 2019 Informa UK Limited, trading as Taylor & Francis Group.


  • Cognitive tutor
  • collaborative storytelling
  • technology in conflict

ASJC Scopus subject areas

  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • General Social Sciences
  • Human-Computer Interaction


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