The early stages of MOF self-assembly are investigated through molecular simulation that allows us to identify key interactions during nucleation at the molecular level. We assess the effects of building unit distribution, solvent, and spectator ions on MIL-101 self-assembly by 100 nslong simulations of more than 780,000 atoms. Clusters of building units are then characterized as an evolving graph. Our results corroborate previous studies, where the solution composition considerably influences the dynamical rearrangement of building units. Consequently, our conclusions confirm these phenomena at large length scales where the complexity is significantly increased. This increased complexity can be deconvoluted through graph theory which we use to monitor and characterize growth at the early stages by projecting trajectories of atomic positions on lower-dimension graphs. The graphs are used to interpret how the connectivity, size, and morphology of clusters evolve during assembly. As a result, this work sets the base for further analysis of nucleation using data science to evaluate dynamics as the propagation of a coarse-grained graph model.