This approach demonstrates enhanced efficiency in achieving structural balance in social computing networks, implying better interpretability of relationships.
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.
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Jiao et al. (2026) studied this question.
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