Computational research analyzes peacebuilding narratives in South Sudan, indicating shifts in conflict understanding over time.
This original research article applies computational methods from computer science to the interdisciplinary study of conflict and peace in South Sudan. It employs natural language processing (NLP) techniques to analyse a large corpus of public-facing documents, including peace agreements, government reports, and international organisation briefings from 2018 to 2023. The study quantitatively maps the evolution of key conflict drivers, peacebuilding priorities, and stakeholder narratives over time. The results reveal significant thematic shifts and persistent discursive gaps between localised grievances and internationally-led peace frameworks. The discussion critically evaluates the utility of computational tools for conflict analysis, arguing for their role in identifying latent patterns and biases within peacebuilding discourse, thereby offering novel evidence for refining conflict-sensitive interventions.
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Abraham Kuol Nyuon (Ph.D) (2026) studied this question.
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