Towards an LLM-powered Social Digital Twinning Platform

• URL: http://arxiv.org/abs/2505.10681v1
• Date: Thu, 15 May 2025 19:58:50 GMT
• Title: Towards an LLM-powered Social Digital Twinning Platform
• Authors: Önder Gürcan, Vanja Falck, Markus G. Rousseau, Larissa L. Lima,
• Abstract summary: Social Digital Twinner is a social simulation tool for exploring plausible effects of what-if scenarios in complex adaptive social systems.<n>The architecture is composed of three seamlessly integrated parts: a data infrastructure featuring real-world data and a synthetic population of citizens.<n>We demonstrate the tool's interactive capabilities by addressing the critical issue of youth school dropouts in Kragero, Norway.
• Score: 0.3499870393443268
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present Social Digital Twinner, an innovative social simulation tool for exploring plausible effects of what-if scenarios in complex adaptive social systems. The architecture is composed of three seamlessly integrated parts: a data infrastructure featuring real-world data and a multi-dimensionally representative synthetic population of citizens, an LLM-enabled agent-based simulation engine, and a user interface that enable intuitive, natural language interactions with the simulation engine and the artificial agents (i.e. citizens). Social Digital Twinner facilitates real-time engagement and empowers stakeholders to collaboratively design, test, and refine intervention measures. The approach is promoting a data-driven and evidence-based approach to societal problem-solving. We demonstrate the tool's interactive capabilities by addressing the critical issue of youth school dropouts in Kragero, Norway, showcasing its ability to create and execute a dedicated social digital twin using natural language.

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