Content and Causality in Influence Networks

Many of us are interested in whether "networks matter." Whether in the spread of disease, the diffusion of information, the propagation of behavioral contagions, the effectiveness of viral marketing, or the magnitude of peer effects in a variety of settings, two key questions must be answered before we can understand whether networks matter: 1) how the content that flows through networks affects the patterns of outcomes we see across nodes and 2) whether the statistical relationships we observe can be interpreted causally. Aral will review what we know and where research might go with respect to content and causality in networks. He will provide two examples from each area to structure the discussion: One from an analysis of email networks and the information content that flows through them at a mid-sized executive recruiting firm and the other from a randomized field experiment on a popular social networking website that tests the effectiveness of "viral product design" strategies in creating peer influence and social contagion among the 1.4 million friends of 9,687 experimental users.