Diffusion of innovations in social networks

While social networks do affect diffusion of innovations, the exact nature of these effects are far from clear, and, in many cases, there exist conflicting hypotheses among researchers. In this paper, we focus on the linear threshold model where each individual requires exposure to (potentially) multiple sources of adoption in her neighborhood before adopting the innovation herself. In contrast with the conclusions in the literature, our bounds suggest that innovations might spread further across networks with a smaller degree of clustering. We provide both analytical evidence and simulations for our claims. Finally, we propose an extension for the linear threshold model to better capture the notion of path dependence, i.e., a few minor shocks along the way could alter the course of diffusion significantly.