Supporting peace negotiations in the Yemen war through machine learning

• DOI: 10.1017/dap.2022.19
• Publication Date: 2022-09-02T07:30:31Z
• Authors: Miguel Arana-Catania; Felix-Anselm van ...; Rob Procter
• Keywords: Conflict analysis; Transformative mediation; Identification; Conflict resolution research; Conflict Transformation; Party-directed mediation

Abstract Today’s conflicts are becoming increasingly complex, fluid, and fragmented, often involving a host of national international actors with multiple divergent interests. This development poses significant challenges for conflict mediation, as mediators struggle to make sense dynamics, such the range parties evolution their political positions, distinction between relevant less in peace-making, or identification key issues interdependence. International peace efforts appear ill-equipped successfully address these challenges. While technology is already being experimented used related fields, predicting information gathering, attention has been given how can contribute mediation. case study contributes emerging research on use state-of-the-art machine learning technologies techniques mediation processes. Using dialogue transcripts from negotiations Yemen, this shows machine-learning effectively support mediating teams by providing them tools knowledge management, extraction analysis. Apart illustrating potential article also emphasizes importance interdisciplinary participatory, cocreation methodology context-sensitive targeted ensure meaningful responsible implementation.