Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation

Fuente: arXiv
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Autori principali: Zancanaro, Massimo, Stock, Oliviero, Schiavo, Gianluca, Cappelletti, Alessandro, Gehrmann, Sebastian, Canetti, Daphna, Shaked, Ohad, Fachter, Shani, Yifat, Rachel, Mimran, Ravit, L., Patrice, Weiss
Natura: Preprint
Pubblicazione: 2019
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author Zancanaro, Massimo
Stock, Oliviero
Schiavo, Gianluca
Cappelletti, Alessandro
Gehrmann, Sebastian
Canetti, Daphna
Shaked, Ohad
Fachter, Shani
Yifat, Rachel
Mimran, Ravit
L., Patrice
Weiss
author_facet Zancanaro, Massimo
Stock, Oliviero
Schiavo, Gianluca
Cappelletti, Alessandro
Gehrmann, Sebastian
Canetti, Daphna
Shaked, Ohad
Fachter, Shani
Yifat, Rachel
Mimran, Ravit
L., Patrice
Weiss
contents 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.
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id arxiv_https___arxiv_org_abs_1906_11597
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation
Zancanaro, Massimo
Stock, Oliviero
Schiavo, Gianluca
Cappelletti, Alessandro
Gehrmann, Sebastian
Canetti, Daphna
Shaked, Ohad
Fachter, Shani
Yifat, Rachel
Mimran, Ravit
L., Patrice
Weiss
Human-Computer Interaction
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.
title Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation
topic Human-Computer Interaction
url https://arxiv.org/abs/1906.11597