arXiv:2606.11482v1 Announce Type: cross Abstract: Understanding and predicting how social beliefs evolve in response to events -- from policy changes to scientific breakthroughs -- remains a fundamental challenge in social science. Given LLMs' commonsense knowledge and social intelligence, we ask: Can LLMs model the dynamics of social beliefs following social events? In this work, we introduce the concept of the Social World Model (SWM), a general framework designed to capture how social beliefs evolve in response to major events. SWM learns state-transition functions for social beliefs by min
The increasing sophistication of LLMs in common sense reasoning and social intelligence makes them viable tools for modeling complex social dynamics, leading to this research at the current stage of AI development.
This work introduces a novel framework for understanding and predicting social belief evolution, offering new tools for social scientists and potentially enabling more accurate forecasting of societal responses to major events.
The ability to model social belief evolution with AI shifts from purely human-driven analysis to potentially AI-assisted or even AI-driven predictive capabilities in social sciences.
- · Social scientists
- · AI researchers
- · Policy makers
- · Social media platforms
- · Traditional social modeling techniques
- · Organizations slow to adopt AI for social analysis
LLMs can be used to simulate and predict social responses to various real-world events.
Improved predictive power of social events could inform more effective policy-making and public communication strategies.
The development of 'social world models' could lead to AI systems that understand and potentially influence human collective behavior on a large scale.
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