LL4G is a novel framework that leverages large language models to dynamically optimize graph neural networks for more accurate personality detection from social media text.

• Addresses limitations of static graphs by creating dynamic node representations from rich semantic features
• Employs self-supervised learning to improve graph structure without additional labeling
• Enhances the quality of personality detection in sparse or noisy social media data
• Demonstrates practical applications for security profiling and user behavior analysis

This research has significant implications for security applications, enabling more robust user profiling, improved authentication systems, and enhanced threat detection through better personality assessment.

LL4G: Self-Supervised Dynamic Optimization for Graph-Based Personality Detection