In this study, we build and test a stochastic, agent-based model of information diffusion, called dFusion. The model incorporates diffusion research and social network analysis into a framework that is consistent with the findings of digital divide and knowledge gap research. Using three separate real-world data sets, our model demonstrates clear causal relationships between social structure, communication network structure, and the degree of "information equality" (relatively equivalent speed of access to salient information) within a given social network. By focusing on differential, rather than absolute, speed of access to information, we hope to create an evaluative framework for information technology investment that accurately and comprehensively predicts the effects of such interventions on social equality.