In the context of social system resilience, the role of information negentropy—a measure of order and structural stability—remains underexplored during emergencies. This study investigates the evolutionary mechanisms of information negentropy under crisis conditions, aiming to quantify how emergencies disrupt and reshape social order through dual internal and external feedback. By integrating dissipative structure theory with a dynamic differential equation model, we propose a novel framework that captures the interplay between entropy increase and negentropy production. The model incorporates internal system dynamics (parameterized by \(\:\alpha\:\) ) and external behavioral influences (parameterized by \(\:\beta\:\) ), simulating how crises trigger transitions in social systems via “double-S” or “multi-S” evolutionary trajectories. Empirical validation using Baidu Index data from five brand-related public opinion crises demonstrates the model’s predictive accuracy, revealing that high-quality information dissemination and coordinated public behavior significantly amplify negentropy accumulation. Key findings indicate that emergencies elevate the upper limit of information negentropy by a factor of \(\:{H}_{\infty\:}\) , enabling systemic upgrades rather than mere disorder suppression. This study advances crisis management strategies by emphasizing proactive negentropy activation, offering actionable insights for enhancing social adaptability through real-time monitoring and parameter optimization. This work bridges theoretical gaps in entropy-driven social dynamics and provides a computational toolset for fostering resilience in complex information ecosystems.
