Abstract
In this chapter, we focus on perhaps the two most prevalent diffusion models in computer science—the independent cascade and linear threshold models. We describe different properties of these models and how these properties affect solving problems such as influence maximization and influence spread. We describe approaches to address influence maximization problem in independent cascade model and linear threshold model that rely on the maximization of submodular functions—as well as extensions to these approaches for larger datasets.
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