B1705
Title: Stochastic differential equation modeling of social influence in networks
Authors: Nynke Niezink - Carnegie Mellon University (United States) [presenting]
Abstract: People, organizations and countries are examples of social actors, operating within networks of interdependencies. The attributes of social actors, such as physical, psychological or performance measures, can be affected by the actors to whom they are connected, a process generally known as social contagion or social influence. We present a new methodology for the estimation of social influence effects on static networks, using stochastic differential equation modeling. To estimate the model, we propose a computationally efficient likelihood evaluation method that avoids inverting very large matrices.
