We use data on a real, large-scale social network of 27 million individuals interacting daily, together with the day-by-day adoption of a new mobile service product, to inform, build and analyze data-driven simulations of the effectiveness of seeding (network targeting) strategies under...

We examine what drives the diffusion of different types of information through email networks and the effects of these diffusion patterns on the productivity and performance of information workers. In particular, we ask: What predicts the likelihood of an individual becoming aware of a strategic...

Identifying causal estimates of peer-to-peer influence in networks is critical to marketing strategy, public policy and beyond. Unfortunately, separating correlation from causation in networked data is complicated. We argue that randomized experimentation in networks, made possible by the...

Social network theories (e.g. Granovetter 1973, Burt 1992) and information richness theory (Daft & Lengel 1987) have both been used independently to understand knowledge transfer in information intensive work settings. Social network theories explain how network structures covary with the...