The field of network analysis and decentralized systems is witnessing significant advancements, with a growing focus on developing innovative frameworks and methods to optimize network dynamics and improve decentralization. Researchers are exploring new approaches to centrality measures, optimal intervention strategies, and fair allocation methods, which are crucial for managing complex networks and decentralized systems. These developments have the potential to enhance our understanding of network behavior, improve the efficiency of decentralized systems, and promote fairness and resilience in various applications. Noteworthy papers in this area include: Structure-Aware Optimal Intervention for Rumor Dynamics on Networks, which proposes a node-level, time-varying optimal intervention framework for rumor propagation in social networks. U-centrality, a novel centrality measure that quantifies a node's ability to unify the agents' state in dynamic environments. Deep Learning-Accelerated Shapley Value for Fair Allocation in Power Systems, which presents a scalable Shapley value approximation framework for fair allocation in power systems. GPoS: Geospatially-aware Proof of Stake, which proposes a geospatially aware proof of stake protocol to improve geospatial decentralization in blockchains.