This thesis studies a problem that has been proposed as a novel way to disrupt communication networks: the load maximization problem. The load on a member of a network represents the amount of communication that the member is forced to be involved in. By maximizing the load on an important member of the network, we hope to increase that member's visibility and susceptibility to capture. In this thesis we characterize load as a combinatorial property of graphs and expose possible connections between load and spectral graph theory. We specifically describe the load and how it changes in several canonical classes of graphs and determine the range of values that the load can take on. We also consider a connection between load and liquid paint flow and use this connection to build a heuristic solver for the load maximization problem. We conclude with a detailed discussion of open questions for future work.