Distributed agent-based modeling (ABM) simulations are often deployed in high-performance environments to emulate complex systems. In non-spatial ABM simulations, agent relationships are represented by a graph structure. The distribution of this graph among processing elements (PEs) significantly impacts the performance of the simulation. Moreover, none of the existing distributed ABM frameworks provide dynamic load balancing for non-spatial ABM simulations based on complex networks. This paper proposes a novel hierarchical approach for dynamic load balancing in non-spatial ABM simulations using multilevel graph partitioning. As a first step toward our goal, we implement two distributed algorithms based on the Label Propagation Algorithm (LPA) to be used for the coarsening of the simulation graph. The effectiveness of these approaches is briefly evaluated through performance and quality metrics.