A Prospective Method for the Dynamic Transformation of Structural Balance in Fully Signed Networks

Structural balance in fully signed networks, integrating both individual attributes and relationships, represents a critical challenge in social computing; however, its dynamic transformation remains underexplored. This study extends structural balance theory by incorporating node attributes and formulating a mathematical framework for optimizing balance dynamics in fully signed networks. A memetic algorithm is designed to achieve structural balance with minimal cost. Evaluations on both synthetic and real-world networks demonstrate the proposed method's effectiveness, efficiency, and social interpretability.