We give an introduction to the use of logical tools in understanding social influence and social networks phenomena. Individuals often form their opinions by interpreting the behavior of others around them, and by reasoning about how those others have formed their opinions. This leads to several well-known herd phenomena, such as informational cascades, bystander effect, pluralistic ignorance, bubbles, and polarization. For instance, in the case of informational cascades, agents in a sequence imitate each other's choices despite having diverging private evidence, sometimes leading the whole community to make the worst possible choice. Similar cascading mechanisms are at the heart of social networks diffusion phenomena.

We first show how an epistemic logic modeling allows to understand the conditions for such cascades to form, as well as their inescapability. We then turn to what logical tools can do for understanding information flow and influence in social networks. We illustrate how extremely simplified models might yield surprising new results, for instance about stabilization conditions of diffusion processes.